<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Martínez-Nava, Gabriela Angélica</style></author><author><style face="normal" font="default" size="100%">Altamirano-Molina, Efren</style></author><author><style face="normal" font="default" size="100%">Vázquez-Mellado, Janitzia</style></author><author><style face="normal" font="default" size="100%">Casimiro-Soriguer, Carlos S</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Lozada-Pérez, Carlos</style></author><author><style face="normal" font="default" size="100%">Herrera-López, Brígida</style></author><author><style face="normal" font="default" size="100%">Martínez-Gómez, Laura Edith</style></author><author><style face="normal" font="default" size="100%">Martínez-Armenta, Carlos</style></author><author><style face="normal" font="default" size="100%">Guido-Gómora, Dafne Lissete</style></author><author><style face="normal" font="default" size="100%">Valle-Gutiérrez, Sarahí</style></author><author><style face="normal" font="default" size="100%">Suarez-Ahedo, Carlos</style></author><author><style face="normal" font="default" size="100%">Camacho-Rea, María Del Carmen</style></author><author><style face="normal" font="default" size="100%">Martínez-García, Mireya</style></author><author><style face="normal" font="default" size="100%">Gutiérrez-Esparza, Guadalupe</style></author><author><style face="normal" font="default" size="100%">Amezcua-Guerra, Luis M</style></author><author><style face="normal" font="default" size="100%">Zamudio-Cuevas, Yessica</style></author><author><style face="normal" font="default" size="100%">Martínez-Flores, Karina</style></author><author><style face="normal" font="default" size="100%">Fernández-Torres, Javier</style></author><author><style face="normal" font="default" size="100%">Burguete-García, Ana I</style></author><author><style face="normal" font="default" size="100%">Orbe-Orihuela, Yaneth Citlalli</style></author><author><style face="normal" font="default" size="100%">Lagunas-Martínez, Alfredo</style></author><author><style face="normal" font="default" size="100%">Méndez-Salazar, Eder Orlando</style></author><author><style face="normal" font="default" size="100%">Francisco-Balderas, Adriana</style></author><author><style face="normal" font="default" size="100%">Palacios-González, Berenice</style></author><author><style face="normal" font="default" size="100%">Pineda, Carlos</style></author><author><style face="normal" font="default" size="100%">López-Reyes, Alberto</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Metatranscriptomic analysis reveals gut microbiome bacterial genes in pyruvate and amino acid metabolism associated with hyperuricemia and gout in humans.</style></title><secondary-title><style face="normal" font="default" size="100%">Sci Rep</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Sci Rep</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Amino Acids</style></keyword><keyword><style  face="normal" font="default" size="100%">Bacteria</style></keyword><keyword><style  face="normal" font="default" size="100%">Case-Control Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Feces</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gastrointestinal Microbiome</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Genes, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">Gout</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Hyperuricemia</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Pyruvic Acid</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcriptome</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2025</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2025 Mar 22</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">15</style></volume><pages><style face="normal" font="default" size="100%">9981</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Several pathologies with metabolic origin, such as hyperuricemia and gout, have been associated with the gut microbiota taxonomic profile. However, there is no evidence of which bacterial genes are being expressed in the gut microbiome, and of their potential effects on hyperuricemia and gout. We sequenced the RNA of 26 fecal samples from 10 healthy normouricemic controls, 10 with asymptomatic hyperuricemia (AH), and six gout patients. The coding sequences were mapped to KEGG orthologues (KO). We compared the expression levels using generalized linear models and validated the expression of four KO in a larger sample by qRT-PCR. A distinct genetic expression pattern was identified among groups. AH individuals and gout patients showed an over-expression of KOs mainly related to pyruvate metabolism (Log2foldchange &gt; 23, p-adj ≤ 3.56 × 10), the pentose pathway (Log2foldchange &gt; 24, p-adj &lt; 1.10 × 10) and purine metabolism (Log2foldchange &gt; 22, p-adj &lt; 1.25 × 10). AH subjects had lower expression of KO related to glycine metabolism (Log2foldchange=-18, p-adj &lt; 1.72 × 10) than controls. Gout patients had lower expression (Log2foldchange=-22.42, p-adj &lt; 3.31 × 10) of a KO involved in phenylalanine biosynthesis, in comparison to controls and AH subjects. The over-expression seen for the KO related to pyruvate metabolism and the pentose pathway in gout patients´ microbiome was validated. There is a differential gene expression pattern in the gut microbiome of normouricemic individuals, AH subjects and gout patients. These differences are mainly located in metabolic pathways involved in acetate precursors and bioavailability of amino acids.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Esteban-Medina, Marina</style></author><author><style face="normal" font="default" size="100%">Loucera, Carlos</style></author><author><style face="normal" font="default" size="100%">Rian, Kinza</style></author><author><style face="normal" font="default" size="100%">Velasco, Sheyla</style></author><author><style face="normal" font="default" size="100%">Olivares-González, Lorena</style></author><author><style face="normal" font="default" size="100%">Rodrigo, Regina</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The mechanistic functional landscape of retinitis pigmentosa: a machine learning-driven approach to therapeutic target discovery.</style></title><secondary-title><style face="normal" font="default" size="100%">J Transl Med</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J Transl Med</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Mice</style></keyword><keyword><style  face="normal" font="default" size="100%">Retinitis pigmentosa</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal Transduction</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2024 Feb 06</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">22</style></volume><pages><style face="normal" font="default" size="100%">139</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Retinitis pigmentosa is the prevailing genetic cause of blindness in developed nations with no effective treatments. In the pursuit of unraveling the intricate dynamics underlying this complex disease, mechanistic models emerge as a tool of proven efficiency rooted in systems biology, to elucidate the interplay between RP genes and their mechanisms. The integration of mechanistic models and drug-target interactions under the umbrella of machine learning methodologies provides a multifaceted approach that can boost the discovery of novel therapeutic targets, facilitating further drug repurposing in RP.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;By mapping Retinitis Pigmentosa-related genes (obtained from Orphanet, OMIM and HPO databases) onto KEGG signaling pathways, a collection of signaling functional circuits encompassing Retinitis Pigmentosa molecular mechanisms was defined. Next, a mechanistic model of the so-defined disease map, where the effects of interventions can be simulated, was built. Then, an explainable multi-output random forest regressor was trained using normal tissue transcriptomic data to learn causal connections between targets of approved drugs from DrugBank and the functional circuits of the mechanistic disease map. Selected target genes involvement were validated on rd10 mice, a murine model of Retinitis Pigmentosa.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;A mechanistic functional map of Retinitis Pigmentosa was constructed resulting in 226 functional circuits belonging to 40 KEGG signaling pathways. The method predicted 109 targets of approved drugs in use with a potential effect over circuits corresponding to nine hallmarks identified. Five of those targets were selected and experimentally validated in rd10 mice: Gabre, Gabra1 (GABARα1 protein), Slc12a5 (KCC2 protein), Grin1 (NR1 protein) and Glr2a. As a result, we provide a resource to evaluate the potential impact of drug target genes in Retinitis Pigmentosa.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;The possibility of building actionable disease models in combination with machine learning algorithms to learn causal drug-disease interactions opens new avenues for boosting drug discovery. Such mechanistically-based hypotheses can guide and accelerate the experimental validations prioritizing drug target candidates. In this work, a mechanistic model describing the functional disease map of Retinitis Pigmentosa was developed, identifying five promising therapeutic candidates targeted by approved drug. Further experimental validation will demonstrate the efficiency of this approach for a systematic application to other rare diseases.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Casimiro-Soriguer, Carlos S</style></author><author><style face="normal" font="default" size="100%">Perez-Florido, Javier</style></author><author><style face="normal" font="default" size="100%">Lara, María</style></author><author><style face="normal" font="default" size="100%">Camacho-Martinez, Pedro</style></author><author><style face="normal" font="default" size="100%">Merino-Diaz, Laura</style></author><author><style face="normal" font="default" size="100%">Pupo-Ledo, Inmaculada</style></author><author><style face="normal" font="default" size="100%">de Salazar, Adolfo</style></author><author><style face="normal" font="default" size="100%">Fuentes, Ana</style></author><author><style face="normal" font="default" size="100%">Viñuela, Laura</style></author><author><style face="normal" font="default" size="100%">Chueca, Natalia</style></author><author><style face="normal" font="default" size="100%">Martinez-Martinez, Luis</style></author><author><style face="normal" font="default" size="100%">Lorusso, Nicola</style></author><author><style face="normal" font="default" size="100%">Lepe, Jose A</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">García, Federico</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Molecular and phylogenetic characterization of the monkeypox outbreak in the South of Spain.</style></title><secondary-title><style face="normal" font="default" size="100%">Health Sci Rep</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Health Sci Rep</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2024 Mar</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">7</style></volume><pages><style face="normal" font="default" size="100%">e1965</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND AND AIM: &lt;/b&gt;Until the May 2022 Monkeypox (MPXV) outbreak, which spread rapidly to many non-endemic countries, the virus was considered a viral zoonosis limited to some African countries. The Andalusian circuit of genomic surveillance was rapidly applied to characterize the MPXV outbreak in the South of Spain.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;Whole genome sequencing was used to obtain the genomic profiles of samples collected across the south of Spain, representative of all the provinces of Andalusia. Phylogenetic analysis was used to study the relationship of the isolates and the available sequences of the 2022 outbreak.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;Whole genome sequencing of a total of 160 MPXV viruses from the different provinces that reported cases were obtained. Interestingly, we report the sequences of MPXV viruses obtained from two patients who died. While one of the isolates bore no noteworthy mutations that explain a potential heightened virulence, in another patient the second consecutive genome sequence, performed after the administration of tecovirimat, uncovered a mutation within the A0A7H0DN30 gene, known to be a prime target for tecovirimat in its Vaccinia counterpart. In general, a low number of mutations were observed in the sequences reported, which were very similar to the reference of the 2022 outbreak (OX044336), as expected from a DNA virus. The samples likely correspond to several introductions of the circulating MPXV viruses from the last outbreak. The virus sequenced from one of the two patients that died presented a mutation in a gene that bears potential connections to drug resistance. This mutation was absent in the initial sequencing before treatment.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pérez-Gutiérrez, Ana M</style></author><author><style face="normal" font="default" size="100%">Carmona, Rosario</style></author><author><style face="normal" font="default" size="100%">Loucera, Carlos</style></author><author><style face="normal" font="default" size="100%">Cervilla, Jorge A</style></author><author><style face="normal" font="default" size="100%">Gutiérrez, Blanca</style></author><author><style face="normal" font="default" size="100%">Molina, Esther</style></author><author><style face="normal" font="default" size="100%">López-López, Daniel</style></author><author><style face="normal" font="default" size="100%">Perez-Florido, Javier</style></author><author><style face="normal" font="default" size="100%">Zarza-Rebollo, Juan Antonio</style></author><author><style face="normal" font="default" size="100%">López-Isac, Elena</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Martinez-Gonzalez, Luis Javier</style></author><author><style face="normal" font="default" size="100%">Rivera, Margarita</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mutational landscape of risk variants in comorbid depression and obesity: a next-generation sequencing approach.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol Psychiatry</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Mol Psychiatry</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2024 May 28</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Major depression (MD) and obesity are complex genetic disorders that are frequently comorbid. However, the study of both diseases concurrently remains poorly addressed and therefore the underlying genetic mechanisms involved in this comorbidity remain largely unknown. Here we examine the contribution of common and rare variants to this comorbidity through a next-generation sequencing (NGS) approach. Specific genomic regions of interest in MD and obesity were sequenced in a group of 654 individuals from the PISMA-ep epidemiological study. We obtained variants across the entire frequency spectrum and assessed their association with comorbid MD and obesity, both at variant and gene levels. We identified 55 independent common variants and a burden of rare variants in 4 genes (PARK2, FGF21, HIST1H3D and RSRC1) associated with the comorbid phenotype. Follow-up analyses revealed significantly enriched gene-sets associated with biological processes and pathways involved in metabolic dysregulation, hormone signaling and cell cycle regulation. Our results suggest that, while risk variants specific to the comorbid phenotype have been identified, the genes functionally impacted by the risk variants share cell biological processes and signaling pathways with MD and obesity phenotypes separately. To the best of our knowledge, this is the first study involving a targeted sequencing approach toward the study of the comorbid MD and obesity. The framework presented here allowed a deep characterization of the genetics of the co-occurring MD and obesity, revealing insights into the mutational and functional profile that underlies this comorbidity and contributing to a better understanding of the relationship between these two disabling disorders.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sola-García, Alejandro</style></author><author><style face="normal" font="default" size="100%">Cáliz-Molina, María Ángeles</style></author><author><style face="normal" font="default" size="100%">Espadas, Isabel</style></author><author><style face="normal" font="default" size="100%">Petr, Michael</style></author><author><style face="normal" font="default" size="100%">Panadero-Morón, Concepción</style></author><author><style face="normal" font="default" size="100%">González-Morán, Daniel</style></author><author><style face="normal" font="default" size="100%">Martín-Vázquez, María Eugenia</style></author><author><style face="normal" font="default" size="100%">Narbona-Pérez, Álvaro Jesús</style></author><author><style face="normal" font="default" size="100%">López-Noriega, Livia</style></author><author><style face="normal" font="default" size="100%">Martínez-Corrales, Guillermo</style></author><author><style face="normal" font="default" size="100%">López-Fernández-Sobrino, Raúl</style></author><author><style face="normal" font="default" size="100%">Carmona-Marin, Lina M</style></author><author><style face="normal" font="default" size="100%">Martínez-Force, Enrique</style></author><author><style face="normal" font="default" size="100%">Yanes, Oscar</style></author><author><style face="normal" font="default" size="100%">Vinaixa, Maria</style></author><author><style face="normal" font="default" size="100%">López-López, Daniel</style></author><author><style face="normal" font="default" size="100%">Reyes, José Carlos</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Martín, Franz</style></author><author><style face="normal" font="default" size="100%">Gauthier, Benoit R</style></author><author><style face="normal" font="default" size="100%">Scheibye-Knudsen, Morten</style></author><author><style face="normal" font="default" size="100%">Capilla-González, Vivian</style></author><author><style face="normal" font="default" size="100%">Martín-Montalvo, Alejandro</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Metabolic reprogramming by Acly inhibition using SB-204990 alters glucoregulation and modulates molecular mechanisms associated with aging.</style></title><secondary-title><style face="normal" font="default" size="100%">Commun Biol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Commun Biol</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2023 Mar 08</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">250</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;ATP-citrate lyase is a central integrator of cellular metabolism in the interface of protein, carbohydrate, and lipid metabolism. The physiological consequences as well as the molecular mechanisms orchestrating the response to long-term pharmacologically induced Acly inhibition are unknown. We report here that the Acly inhibitor SB-204990 improves metabolic health and physical strength in wild-type mice when fed with a high-fat diet, while in mice fed with healthy diet results in metabolic imbalance and moderated insulin resistance. By applying a multiomic approach using untargeted metabolomics, transcriptomics, and proteomics, we determined that, in vivo, SB-204990 plays a role in the regulation of molecular mechanisms associated with aging, such as energy metabolism, mitochondrial function, mTOR signaling, and folate cycle, while global alterations on histone acetylation are absent. Our findings indicate a mechanism for regulating molecular pathways of aging that prevents the development of metabolic abnormalities associated with unhealthy dieting. This strategy might be explored for devising therapeutic approaches to prevent metabolic diseases.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Corrales, Patricia</style></author><author><style face="normal" font="default" size="100%">Martin-Taboada, Marina</style></author><author><style face="normal" font="default" size="100%">Vivas-García, Yurena</style></author><author><style face="normal" font="default" size="100%">Torres, Lucia</style></author><author><style face="normal" font="default" size="100%">Ramirez-Jimenez, Laura</style></author><author><style face="normal" font="default" size="100%">Lopez, Yamila</style></author><author><style face="normal" font="default" size="100%">Horrillo, Daniel</style></author><author><style face="normal" font="default" size="100%">Vila-Bedmar, Rocio</style></author><author><style face="normal" font="default" size="100%">Barber-Cano, Eloisa</style></author><author><style face="normal" font="default" size="100%">Izquierdo-Lahuerta, Adriana</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Martínez, Carmen</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Ros, Manuel</style></author><author><style face="normal" font="default" size="100%">Medina-Gomez, Gema</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">microRNAs-mediated regulation of insulin signaling in white adipose tissue during aging: Role of caloric restriction.</style></title><secondary-title><style face="normal" font="default" size="100%">Aging Cell</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Aging Cell</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2023 Jul 04</style></date></pub-dates></dates><pages><style face="normal" font="default" size="100%">e13919</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Caloric restriction is a non-pharmacological intervention known to ameliorate the metabolic defects associated with aging, including insulin resistance. The levels of miRNA expression may represent a predictive tool for aging-related alterations. In order to investigate the role of miRNAs underlying insulin resistance in adipose tissue during the early stages of aging, 3- and 12-month-old male animals fed ad libitum, and 12-month-old male animals fed with a 20% caloric restricted diet were used. In this work we demonstrate that specific miRNAs may contribute to the impaired insulin-stimulated glucose metabolism specifically in the subcutaneous white adipose tissue, through the regulation of target genes implicated in the insulin signaling cascade. Moreover, the expression of these miRNAs is modified by caloric restriction in middle-aged animals, in accordance with the improvement of the metabolic state. Overall, our work demonstrates that alterations in posttranscriptional gene expression because of miRNAs dysregulation might represent an endogenous mechanism by which insulin response in the subcutaneous fat depot is already affected at middle age. Importantly, caloric restriction could prevent this modulation, demonstrating that certain miRNAs could constitute potential biomarkers of age-related metabolic alterations.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rian, Kinza</style></author><author><style face="normal" font="default" size="100%">Esteban-Medina, Marina</style></author><author><style face="normal" font="default" size="100%">Hidalgo, Marta R</style></author><author><style face="normal" font="default" size="100%">Cubuk, Cankut</style></author><author><style face="normal" font="default" size="100%">Falco, Matias M</style></author><author><style face="normal" font="default" size="100%">Loucera, Carlos</style></author><author><style face="normal" font="default" size="100%">Gunyel, Devrim</style></author><author><style face="normal" font="default" size="100%">Ostaszewski, Marek</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mechanistic modeling of the SARS-CoV-2 disease map.</style></title><secondary-title><style face="normal" font="default" size="100%">BioData Min</style></secondary-title><alt-title><style face="normal" font="default" size="100%">BioData Min</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 Jan 21</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">5</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Here we present a web interface that implements a comprehensive mechanistic model of the SARS-CoV-2 disease map. In this framework, the detailed activity of the human signaling circuits related to the viral infection, covering from the entry and replication mechanisms to the downstream consequences as inflammation and antigenic response, can be inferred from gene expression experiments. Moreover, the effect of potential interventions, such as knock-downs, or drug effects (currently the system models the effect of more than 8000 DrugBank drugs) can be studied. This freely available tool not only provides an unprecedentedly detailed view of the mechanisms of viral invasion and the consequences in the cell but has also the potential of becoming an invaluable asset in the search for efficient antiviral treatments.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/33478554?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Millán-Esteban, David</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">García-Casado, Zaida</style></author><author><style face="normal" font="default" size="100%">Manrique-Silva, Esperanza</style></author><author><style face="normal" font="default" size="100%">Requena, Celia</style></author><author><style face="normal" font="default" size="100%">Bañuls, José</style></author><author><style face="normal" font="default" size="100%">Lopez-Guerrero, Jose Antonio</style></author><author><style face="normal" font="default" size="100%">Rodríguez-Hernández, Aranzazu</style></author><author><style face="normal" font="default" size="100%">Traves, Víctor</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Virós, Amaya</style></author><author><style face="normal" font="default" size="100%">Kumar, Rajiv</style></author><author><style face="normal" font="default" size="100%">Nagore, Eduardo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mutational Characterization of Cutaneous Melanoma Supports Divergent Pathways Model for Melanoma Development.</style></title><secondary-title><style face="normal" font="default" size="100%">Cancers (Basel)</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Cancers (Basel)</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 Oct 18</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">13</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;According to the divergent pathway model, cutaneous melanoma comprises a nevogenic group with a propensity to melanocyte proliferation and another one associated with cumulative solar damage (CSD). While characterized clinically and epidemiologically, the differences in the molecular profiles between the groups have remained primarily uninvestigated. This study has used a custom gene panel and bioinformatics tools to investigate the potential molecular differences in a thoroughly characterized cohort of 119 melanoma patients belonging to nevogenic and CSD groups. We found that the nevogenic melanomas had a restricted set of mutations, with the prominently mutated gene being . The CSD melanomas, in contrast, showed mutations in a diverse group of genes that included , , , and . We thus provide evidence that nevogenic and CSD melanomas constitute different biological entities and highlight the need to explore new targeted therapies.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">20</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Falco, Matias M</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Loucera, Carlos</style></author><author><style face="normal" font="default" size="100%">Hidalgo, Marta R</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mechanistic models of signaling pathways deconvolute the glioblastoma single-cell functional landscapeAbstract</style></title><secondary-title><style face="normal" font="default" size="100%">NAR Cancer</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan-06-2020</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://academic.oup.com/narcancer/article/doi/10.1093/narcan/zcaa011/5862620http://academic.oup.com/narcancer/article-pdf/2/2/zcaa011/33428092/zcaa011.pdfhttp://academic.oup.com/narcancer/article-pdf/2/2/zcaa011/33428092/zcaa011.pdf</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">2</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">2</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cubuk, Cankut</style></author><author><style face="normal" font="default" size="100%">Can, Fatma E</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mechanistic Models of Signaling Pathways Reveal the Drug Action Mechanisms behind Gender-Specific Gene Expression for Cancer Treatments.</style></title><secondary-title><style face="normal" font="default" size="100%">Cells</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Cells</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Neoplastic</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Neoplasms</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal Transduction</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 06 29</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">9</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Despite the existence of differences in gene expression across numerous genes between males and females having been known for a long time, these have been mostly ignored in many studies, including drug development and its therapeutic use. In fact, the consequences of such differences over the disease mechanisms or the drug action mechanisms are completely unknown. Here we applied mechanistic mathematical models of signaling activity to reveal the ultimate functional consequences that gender-specific gene expression activities have over cell functionality and fate. Moreover, we also used the mechanistic modeling framework to simulate the drug interventions and unravel how drug action mechanisms are affected by gender-specific differential gene expression. Interestingly, some cancers have many biological processes significantly affected by these gender-specific differences (e.g., bladder or head and neck carcinomas), while others (e.g., glioblastoma or rectum cancer) are almost insensitive to them. We found that many of these gender-specific differences affect cancer-specific pathways or in physiological signaling pathways, also involved in cancer origin and development. Finally, mechanistic models have the potential to be used for finding alternative therapeutic interventions on the pathways targeted by the drug, which lead to similar results compensating the downstream consequences of gender-specific differences in gene expression.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">7</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32610626?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hidalgo, Marta R</style></author><author><style face="normal" font="default" size="100%">Amadoz, Alicia</style></author><author><style face="normal" font="default" size="100%">Cubuk, Cankut</style></author><author><style face="normal" font="default" size="100%">Carbonell-Caballero, José</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Models of cell signaling uncover molecular mechanisms of high-risk neuroblastoma and predict disease outcome.</style></title><secondary-title><style face="normal" font="default" size="100%">Biol Direct</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Biol Direct</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Computational Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Neoplastic</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">JNK Mitogen-Activated Protein Kinases</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Theoretical</style></keyword><keyword><style  face="normal" font="default" size="100%">Neuroblastoma</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal Transduction</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2018 Aug 22</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">13</style></volume><pages><style face="normal" font="default" size="100%">16</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Despite the progress in neuroblastoma therapies the mortality of high-risk patients is still high (40-50%) and the molecular basis of the disease remains poorly known. Recently, a mathematical model was used to demonstrate that the network regulating stress signaling by the c-Jun N-terminal kinase pathway played a crucial role in survival of patients with neuroblastoma irrespective of their MYCN amplification status. This demonstrates the enormous potential of computational models of biological modules for the discovery of underlying molecular mechanisms of diseases.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;Since signaling is known to be highly relevant in cancer, we have used a computational model of the whole cell signaling network to understand the molecular determinants of bad prognostic in neuroblastoma. Our model produced a comprehensive view of the molecular mechanisms of neuroblastoma tumorigenesis and progression.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSION: &lt;/b&gt;We have also shown how the activity of signaling circuits can be considered a reliable model-based prognostic biomarker.&lt;/p&gt;&lt;p&gt;&lt;b&gt;REVIEWERS: &lt;/b&gt;This article was reviewed by Tim Beissbarth, Wenzhong Xiao and Joanna Polanska. For the full reviews, please go to the Reviewers' comments section.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/30134948?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ibáñez, Mariam</style></author><author><style face="normal" font="default" size="100%">Carbonell-Caballero, José</style></author><author><style face="normal" font="default" size="100%">Such, Esperanza</style></author><author><style face="normal" font="default" size="100%">García-Alonso, Luz</style></author><author><style face="normal" font="default" size="100%">Liquori, Alessandro</style></author><author><style face="normal" font="default" size="100%">López-Pavía, María</style></author><author><style face="normal" font="default" size="100%">LLop, Marta</style></author><author><style face="normal" font="default" size="100%">Alonso, Carmen</style></author><author><style face="normal" font="default" size="100%">Barragán, Eva</style></author><author><style face="normal" font="default" size="100%">Gómez-Seguí, Inés</style></author><author><style face="normal" font="default" size="100%">Neef, Alexander</style></author><author><style face="normal" font="default" size="100%">Hervás, David</style></author><author><style face="normal" font="default" size="100%">Montesinos, Pau</style></author><author><style face="normal" font="default" size="100%">Sanz, Guillermo</style></author><author><style face="normal" font="default" size="100%">Sanz, Miguel Angel</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Cervera, José</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The modular network structure of the mutational landscape of Acute Myeloid Leukemia.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS One</style></secondary-title><alt-title><style face="normal" font="default" size="100%">PLoS One</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Cytodiagnosis</style></keyword><keyword><style  face="normal" font="default" size="100%">Exome Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Regulatory Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Association Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Heterogeneity</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Karyotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Leukemia, Myeloid, Acute</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Neoplasm Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Nucleophosmin</style></keyword><keyword><style  face="normal" font="default" size="100%">Prognosis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2018</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">13</style></volume><pages><style face="normal" font="default" size="100%">e0202926</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Acute myeloid leukemia (AML) is associated with the sequential accumulation of acquired genetic alterations. Although at diagnosis cytogenetic alterations are frequent in AML, roughly 50% of patients present an apparently normal karyotype (NK), leading to a highly heterogeneous prognosis. Due to this significant heterogeneity, it has been suggested that different molecular mechanisms may trigger the disease with diverse prognostic implications. We performed whole-exome sequencing (WES) of tumor-normal matched samples of de novo AML-NK patients lacking mutations in NPM1, CEBPA or FLT3-ITD to identify new gene mutations with potential prognostic and therapeutic relevance to patients with AML. Novel candidate-genes, together with others previously described, were targeted resequenced in an independent cohort of 100 de novo AML patients classified in the cytogenetic intermediate-risk (IR) category. A mean of 4.89 mutations per sample were detected in 73 genes, 35 of which were mutated in more than one patient. After a network enrichment analysis, we defined a single in silico model and established a set of seed-genes that may trigger leukemogenesis in patients with normal karyotype. The high heterogeneity of gene mutations observed in AML patients suggested that a specific alteration could not be as essential as the interaction of deregulated pathways.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">10</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/30303964?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Matalonga, Leslie</style></author><author><style face="normal" font="default" size="100%">Bravo, Miren</style></author><author><style face="normal" font="default" size="100%">Serra-Peinado, Carla</style></author><author><style face="normal" font="default" size="100%">García-Pelegrí, Elisabeth</style></author><author><style face="normal" font="default" size="100%">Ugarteburu, Olatz</style></author><author><style face="normal" font="default" size="100%">Vidal, Silvia</style></author><author><style face="normal" font="default" size="100%">Llambrich, Maria</style></author><author><style face="normal" font="default" size="100%">Quintana, Ester</style></author><author><style face="normal" font="default" size="100%">Fuster-Jorge, Pedro</style></author><author><style face="normal" font="default" size="100%">Gonzalez-Bravo, Maria Nieves</style></author><author><style face="normal" font="default" size="100%">Beltran, Sergi</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">Foulquier, François</style></author><author><style face="normal" font="default" size="100%">Matthijs, Gert</style></author><author><style face="normal" font="default" size="100%">Mills, Philippa</style></author><author><style face="normal" font="default" size="100%">Ribes, Antonia</style></author><author><style face="normal" font="default" size="100%">Egea, Gustavo</style></author><author><style face="normal" font="default" size="100%">Briones, Paz</style></author><author><style face="normal" font="default" size="100%">Tort, Frederic</style></author><author><style face="normal" font="default" size="100%">Girós, Marisa</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mutations in TRAPPC11 are associated with a congenital disorder of glycosylation.</style></title><secondary-title><style face="normal" font="default" size="100%">Hum Mutat</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Hum Mutat</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Abnormalities, Multiple</style></keyword><keyword><style  face="normal" font="default" size="100%">Alleles</style></keyword><keyword><style  face="normal" font="default" size="100%">Amino Acid Substitution</style></keyword><keyword><style  face="normal" font="default" size="100%">Brain</style></keyword><keyword><style  face="normal" font="default" size="100%">Congenital Disorders of Glycosylation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Magnetic Resonance Imaging</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Vesicular Transport Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Whole Genome Sequencing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Feb</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">38</style></volume><pages><style face="normal" font="default" size="100%">148-151</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Congenital disorders of glycosylation (CDG) are a heterogeneous and rapidly growing group of diseases caused by abnormal glycosylation of proteins and/or lipids. Mutations in genes involved in the homeostasis of the endoplasmic reticulum (ER), the Golgi apparatus (GA), and the vesicular trafficking from the ER to the ER-Golgi intermediate compartment (ERGIC) have been found to be associated with CDG. Here, we report a patient with defects in both N- and O-glycosylation combined with a delayed vesicular transport in the GA due to mutations in TRAPPC11, a subunit of the TRAPPIII complex. TRAPPIII is implicated in the anterograde transport from the ER to the ERGIC as well as in the vesicle export from the GA. This report expands the spectrum of genetic alterations associated with CDG, providing new insights for the diagnosis and the understanding of the physiopathological mechanisms underlying glycosylation disorders.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/27862579?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ibáñez, Mariam</style></author><author><style face="normal" font="default" size="100%">Carbonell-Caballero, José</style></author><author><style face="normal" font="default" size="100%">García-Alonso, Luz</style></author><author><style face="normal" font="default" size="100%">Such, Esperanza</style></author><author><style face="normal" font="default" size="100%">Jiménez-Almazán, Jorge</style></author><author><style face="normal" font="default" size="100%">Vidal, Enrique</style></author><author><style face="normal" font="default" size="100%">Barragán, Eva</style></author><author><style face="normal" font="default" size="100%">López-Pavía, María</style></author><author><style face="normal" font="default" size="100%">LLop, Marta</style></author><author><style face="normal" font="default" size="100%">Martín, Iván</style></author><author><style face="normal" font="default" size="100%">Gómez-Seguí, Inés</style></author><author><style face="normal" font="default" size="100%">Montesinos, Pau</style></author><author><style face="normal" font="default" size="100%">Sanz, Miguel A</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Cervera, José</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The Mutational Landscape of Acute Promyelocytic Leukemia Reveals an Interacting Network of Co-Occurrences and Recurrent Mutations.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS One</style></secondary-title><alt-title><style face="normal" font="default" size="100%">PLoS One</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Regulatory Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">INDEL Mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Leukemia, Promyelocytic, Acute</style></keyword><keyword><style  face="normal" font="default" size="100%">mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Mutation Rate</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">Reproducibility of Results</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">e0148346</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Preliminary Acute Promyelocytic Leukemia (APL) whole exome sequencing (WES) studies have identified a huge number of somatic mutations affecting more than a hundred different genes mainly in a non-recurrent manner, suggesting that APL is a heterogeneous disease with secondary relevant changes not yet defined. To extend our knowledge of subtle genetic alterations involved in APL that might cooperate with PML/RARA in the leukemogenic process, we performed a comprehensive analysis of somatic mutations in APL combining WES with sequencing of a custom panel of targeted genes by next-generation sequencing. To select a reduced subset of high confidence candidate driver genes, further in silico analysis were carried out. After prioritization and network analysis we found recurrent deleterious mutations in 8 individual genes (STAG2, U2AF1, SMC1A, USP9X, IKZF1, LYN, MYCBP2 and PTPN11) with a strong potential of being involved in APL pathogenesis. Our network analysis of multiple mutations provides a reliable approach to prioritize genes for additional analysis, improving our knowledge of the leukemogenesis interactome. Additionally, we have defined a functional module in the interactome of APL. The hypothesis is that the number, or the specific combinations, of mutations harbored in each patient might not be as important as the disturbance caused in biological key functions, triggered by several not necessarily recurrent mutations. &lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/26886259?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sevilla, Teresa</style></author><author><style face="normal" font="default" size="100%">Lupo, Vincenzo</style></author><author><style face="normal" font="default" size="100%">Martínez-Rubio, Dolores</style></author><author><style face="normal" font="default" size="100%">Sancho, Paula</style></author><author><style face="normal" font="default" size="100%">Sivera, Rafael</style></author><author><style face="normal" font="default" size="100%">Chumillas, María J</style></author><author><style face="normal" font="default" size="100%">García-Romero, Mar</style></author><author><style face="normal" font="default" size="100%">Pascual-Pascual, Samuel I</style></author><author><style face="normal" font="default" size="100%">Muelas, Nuria</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Vílchez, Juan J</style></author><author><style face="normal" font="default" size="100%">Palau, Francesc</style></author><author><style face="normal" font="default" size="100%">Espinós, Carmen</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mutations in the MORC2 gene cause axonal Charcot-Marie-Tooth disease.</style></title><secondary-title><style face="normal" font="default" size="100%">Brain</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Brain</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Axons</style></keyword><keyword><style  face="normal" font="default" size="100%">Charcot-Marie-Tooth Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">gene expression</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Infant</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Mice</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Pedigree</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Sciatic Nerve</style></keyword><keyword><style  face="normal" font="default" size="100%">Sural Nerve</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">Young Adult</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016 Jan</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">139</style></volume><pages><style face="normal" font="default" size="100%">62-72</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Charcot-Marie-Tooth disease (CMT) is a complex disorder with wide genetic heterogeneity. Here we present a new axonal Charcot-Marie-Tooth disease form, associated with the gene microrchidia family CW-type zinc finger 2 (MORC2). Whole-exome sequencing in a family with autosomal dominant segregation identified the novel MORC2 p.R190W change in four patients. Further mutational screening in our axonal Charcot-Marie-Tooth disease clinical series detected two additional sporadic cases, one patient who also carried the same MORC2 p.R190W mutation and another patient that harboured a MORC2 p.S25L mutation. Genetic and in silico studies strongly supported the pathogenicity of these sequence variants. The phenotype was variable and included patients with congenital or infantile onset, as well as others whose symptoms started in the second decade. The patients with early onset developed a spinal muscular atrophy-like picture, whereas in the later onset cases, the initial symptoms were cramps, distal weakness and sensory impairment. Weakness and atrophy progressed in a random and asymmetric fashion and involved limb girdle muscles, leading to a severe incapacity in adulthood. Sensory loss was always prominent and proportional to disease severity. Electrophysiological studies were consistent with an asymmetric axonal motor and sensory neuropathy, while fasciculations and myokymia were recorded rather frequently by needle electromyography. Sural nerve biopsy revealed pronounced multifocal depletion of myelinated fibres with some regenerative clusters and occasional small onion bulbs. Morc2 is expressed in both axons and Schwann cells of mouse peripheral nerve. Different roles in biological processes have been described for MORC2. As the silencing of Charcot-Marie-Tooth disease genes have been associated with DNA damage response, it is tempting to speculate that a deregulation of this pathway may be linked to the axonal degeneration observed in MORC2 neuropathy, thus adding a new pathogenic mechanism to the long list of causes of Charcot-Marie-Tooth disease. &lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">Pt 1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/26497905?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Manuel Iglesias, Juan</style></author><author><style face="normal" font="default" size="100%">Beloqui, Izaskun</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">Leis, Olatz</style></author><author><style face="normal" font="default" size="100%">Vazquez-Martin, Alejandro</style></author><author><style face="normal" font="default" size="100%">Eguiara, Arrate</style></author><author><style face="normal" font="default" size="100%">Cufi, Silvia</style></author><author><style face="normal" font="default" size="100%">Pavon, Andres</style></author><author><style face="normal" font="default" size="100%">Menendez, Javier A</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Martin, Angel G</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mammosphere formation in breast carcinoma cell lines depends upon expression of E-cadherin.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS One</style></secondary-title><alt-title><style face="normal" font="default" size="100%">PLoS One</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Breast Neoplasms</style></keyword><keyword><style  face="normal" font="default" size="100%">Cadherins</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Line, Tumor</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Proliferation</style></keyword><keyword><style  face="normal" font="default" size="100%">Cluster Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">gene expression</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Neoplastic</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Knockdown Techniques</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">MCF-7 Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Neoplastic Stem Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Spheroids, Cellular</style></keyword><keyword><style  face="normal" font="default" size="100%">Tumor Cells, Cultured</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2013</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">e77281</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Tumors are heterogeneous at the cellular level where the ability to maintain tumor growth resides in discrete cell populations. Floating sphere-forming assays are broadly used to test stem cell activity in tissues, tumors and cell lines. Spheroids are originated from a small population of cells with stem cell features able to grow in suspension culture and behaving as tumorigenic in mice. We tested the ability of eleven common breast cancer cell lines representing the major breast cancer subtypes to grow as mammospheres, measuring the ability to maintain cell viability upon serial non-adherent passage. Only MCF7, T47D, BT474, MDA-MB-436 and JIMT1 were successfully propagated as long-term mammosphere cultures, measured as the increase in the number of viable cells upon serial non-adherent passages. Other cell lines tested (SKBR3, MDA-MB-231, MDA-MB-468 and MDA-MB-435) formed cell clumps that can be disaggregated mechanically, but cell viability drops dramatically on their second passage. HCC1937 and HCC1569 cells formed typical mammospheres, although they could not be propagated as long-term mammosphere cultures. All the sphere forming lines but MDA-MB-436 express E-cadherin on their surface. Knock down of E-cadherin expression in MCF-7 cells abrogated its ability to grow as mammospheres, while re-expression of E-cadherin in SKBR3 cells allow them to form mammospheres. Therefore, the mammosphere assay is suitable to reveal stem like features in breast cancer cell lines that express E-cadherin.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">10</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/24124614?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Manuel Iglesias, Juan</style></author><author><style face="normal" font="default" size="100%">Beloqui, Izaskun</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">Leis, Olatz</style></author><author><style face="normal" font="default" size="100%">Vazquez-Martin, Alejandro</style></author><author><style face="normal" font="default" size="100%">Eguiara, Arrate</style></author><author><style face="normal" font="default" size="100%">Cufi, Silvia</style></author><author><style face="normal" font="default" size="100%">Pavon, Andres</style></author><author><style face="normal" font="default" size="100%">Menendez, Javier A.</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Martin, Angel G.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mammosphere Formation in Breast Carcinoma Cell Lines Depends upon Expression of E-cadherin</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS ONE</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2013/10/04</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1371%2Fjournal.pone.0077281</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Public Library of Science</style></publisher><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">e77281 -</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Tumors are heterogeneous at the cellular level where the ability to maintain tumor growth resides in discrete cell populations. Floating sphere-forming assays are broadly used to test stem cell activity in tissues, tumors and cell lines. Spheroids are originated from a small population of cells with stem cell features able to grow in suspension culture and behaving as tumorigenic in mice. We tested the ability of eleven common breast cancer cell lines representing the major breast cancer subtypes to grow as mammospheres, measuring the ability to maintain cell viability upon serial non-adherent passage. Only MCF7, T47D, BT474, MDA-MB-436 and JIMT1 were successfully propagated as long-term mammosphere cultures, measured as the increase in the number of viable cells upon serial non-adherent passages. Other cell lines tested (SKBR3, MDA-MB-231, MDA-MB-468 and MDA-MB-435) formed cell clumps that can be disaggregated mechanically, but cell viability drops dramatically on their second passage. HCC1937 and HCC1569 cells formed typical mammospheres, although they could not be propagated as long-term mammosphere cultures. All the sphere forming lines but MDA-MB-436 express E-cadherin on their surface. Knock down of E-cadherin expression in MCF-7 cells abrogated its ability to grow as mammospheres, while re-expression of E-cadherin in SKBR3 cells allow them to form mammospheres. Therefore, the mammosphere assay is suitable to reveal stem like features in breast cancer cell lines that express E-cadherin.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gonzalez, Cristina Y.</style></author><author><style face="normal" font="default" size="100%">Bleda, Marta</style></author><author><style face="normal" font="default" size="100%">Salavert, Francisco</style></author><author><style face="normal" font="default" size="100%">Sánchez, Rubén</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Medina, Ignacio</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multicore and Cloud-based Solutions for Genomic Variant Analysis</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 18th International Conference on Parallel Processing Workshops</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">genomic variant analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">multicore</style></keyword><keyword><style  face="normal" font="default" size="100%">mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">OpenMP</style></keyword><keyword><style  face="normal" font="default" size="100%">web service</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/978-3-642-36949-0_30</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer-Verlag</style></publisher><pub-location><style face="normal" font="default" size="100%">Berlin, Heidelberg</style></pub-location><isbn><style face="normal" font="default" size="100%">978-3-642-36948-3</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Carbonell, José</style></author><author><style face="normal" font="default" size="100%">Alloza, Eva</style></author><author><style face="normal" font="default" size="100%">Arce, Pablo</style></author><author><style face="normal" font="default" size="100%">Borrego, Salud</style></author><author><style face="normal" font="default" size="100%">Santoyo, Javier</style></author><author><style face="normal" font="default" size="100%">Ruiz-Ferrer, Macarena</style></author><author><style face="normal" font="default" size="100%">Medina, Ignacio</style></author><author><style face="normal" font="default" size="100%">Jiménez-Almazán, Jorge</style></author><author><style face="normal" font="default" size="100%">Méndez-Vidal, Cristina</style></author><author><style face="normal" font="default" size="100%">González-del Pozo, María</style></author><author><style face="normal" font="default" size="100%">Vela, Alicia</style></author><author><style face="normal" font="default" size="100%">Bhattacharya, Shomi S</style></author><author><style face="normal" font="default" size="100%">Antiňolo, Guillermo</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A map of human microRNA variation uncovers unexpectedly high levels of variability.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome medicine</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">NGS</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2012 Aug 20</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://genomemedicine.com/content/4/8/62/abstract</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">62</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">ABSTRACT: BACKGROUND: MicroRNAs (miRNAs) are key components of the gene regulatory network in many species. During the past few years, these regulatory elements have been shown to be involved in an increasing number and range of diseases. Consequently, the compilation of a comprehensive map of natural variability in healthy population seems an obvious requirement for future research on miRNA-related pathologies. METHODS: Data on 14 populations from the 1000 Genomes Project were analysed, along with new data extracted from 60 exomes of healthy individuals from a southern Spain population, sequenced in the context of the Medical Genome Project, to derive an accurate map of miRNA variability. RESULTS: Despite the common belief that miRNAs are highly conserved elements, analysis of the sequences of the 1,152 individuals indicated that the observed level of variability is double what was expected. A total of 527 variants were found. Among these, 45 variants affected the recognition region of the corresponding miRNA and were found in 43 different miRNAs, 26 of which are known to be involved in 57 diseases. Different parts of the mature structure of the miRNA were affected to different degrees by variants, which suggests the existence of a selective pressure related to the relative functional impact of the change. Moreover, 41 variants showed a significant deviation from the Hardy-Weinberg equilibrium, which supports the existence of a selective process against some alleles. The average number of variants per individual in miRNAs was 28. CONCLUSIONS: Despite an expectation that miRNAs would be highly conserved genomic elements, our study reports a level of variability comparable to that observed for coding genes.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">González-del Pozo, María</style></author><author><style face="normal" font="default" size="100%">Borrego, Salud</style></author><author><style face="normal" font="default" size="100%">Barragán, Isabel</style></author><author><style face="normal" font="default" size="100%">Pieras, Juan I</style></author><author><style face="normal" font="default" size="100%">Santoyo, Javier</style></author><author><style face="normal" font="default" size="100%">Matamala, Nerea</style></author><author><style face="normal" font="default" size="100%">Naranjo, Belén</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Antiňolo, Guillermo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mutation screening of multiple genes in Spanish patients with autosomal recessive retinitis pigmentosa by targeted resequencing.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS One</style></secondary-title><alt-title><style face="normal" font="default" size="100%">PLoS One</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Alleles</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Mutational Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Exons</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome</style></keyword><keyword><style  face="normal" font="default" size="100%">Hispanic or Latino</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Introns</style></keyword><keyword><style  face="normal" font="default" size="100%">Language</style></keyword><keyword><style  face="normal" font="default" size="100%">mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Mutation, Missense</style></keyword><keyword><style  face="normal" font="default" size="100%">Oligonucleotide Array Sequence Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymerase Chain Reaction</style></keyword><keyword><style  face="normal" font="default" size="100%">Reproducibility of Results</style></keyword><keyword><style  face="normal" font="default" size="100%">Retinitis pigmentosa</style></keyword><keyword><style  face="normal" font="default" size="100%">United States</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">e27894</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Retinitis Pigmentosa (RP) is a heterogeneous group of inherited retinal dystrophies characterised ultimately by the loss of photoreceptor cells. RP is the leading cause of visual loss in individuals younger than 60 years, with a prevalence of about 1 in 4000. The molecular genetic diagnosis of autosomal recessive RP (arRP) is challenging due to the large genetic and clinical heterogeneity. Traditional methods for sequencing arRP genes are often laborious and not easily available and a screening technique that enables the rapid detection of the genetic cause would be very helpful in the clinical practice. The goal of this study was to develop and apply microarray-based resequencing technology capable of detecting both known and novel mutations on a single high-throughput platform. Hence, the coding regions and exon/intron boundaries of 16 arRP genes were resequenced using microarrays in 102 Spanish patients with clinical diagnosis of arRP. All the detected variations were confirmed by direct sequencing and potential pathogenicity was assessed by functional predictions and frequency in controls. For validation purposes 4 positive controls for variants consisting of previously identified changes were hybridized on the array. As a result of the screening, we detected 44 variants, of which 15 are very likely pathogenic detected in 14 arRP families (14%). Finally, the design of this array can easily be transformed in an equivalent diagnostic system based on targeted enrichment followed by next generation sequencing.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">12</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/22164218?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jimenez, Rafael C</style></author><author><style face="normal" font="default" size="100%">Salazar, Gustavo A</style></author><author><style face="normal" font="default" size="100%">Gel, Bernat</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Mulder, Nicola</style></author><author><style face="normal" font="default" size="100%">Corpas, Manuel</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">myKaryoView: a light-weight client for visualization of genomic data.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS One</style></secondary-title><alt-title><style face="normal" font="default" size="100%">PLoS One</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Computer Graphics</style></keyword><keyword><style  face="normal" font="default" size="100%">Databases, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Sequence Annotation</style></keyword><keyword><style  face="normal" font="default" size="100%">User-Computer Interface</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">e26345</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The Distributed Annotation System (DAS) is a protocol for easy sharing and integration of biological annotations. In order to visualize feature annotations in a genomic context a client is required. Here we present myKaryoView, a simple light-weight DAS tool for visualization of genomic annotation. myKaryoView has been specifically configured to help analyse data derived from personal genomics, although it can also be used as a generic genome browser visualization. Several well-known data sources are provided to facilitate comparison of known genes and normal variation regions. The navigation experience is enhanced by simultaneous rendering of different levels of detail across chromosomes. A simple interface is provided to allow searches for any SNP, gene or chromosomal region. User-defined DAS data sources may also be added when querying the system. We demonstrate myKaryoView capabilities for adding user-defined sources with a set of genetic profiles of family-related individuals downloaded directly from 23andMe. myKaryoView is a web tool for visualization of genomic data specifically designed for direct-to-consumer genomic data that uses publicly available data distributed throughout the Internet. It does not require data to be held locally and it is capable of rendering any feature as long as it conforms to DAS specifications. Configuration and addition of sources to myKaryoView can be done through the interface. Here we show a proof of principle of myKaryoView's ability to display personal genomics data with 23andMe genome data sources. The tool is available at: http://mykaryoview.com.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">10</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/22046276?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Shi, Leming</style></author><author><style face="normal" font="default" size="100%">Campbell, Gregory</style></author><author><style face="normal" font="default" size="100%">Jones, Wendell D</style></author><author><style face="normal" font="default" size="100%">Campagne, Fabien</style></author><author><style face="normal" font="default" size="100%">Wen, Zhining</style></author><author><style face="normal" font="default" size="100%">Walker, Stephen J</style></author><author><style face="normal" font="default" size="100%">Su, Zhenqiang</style></author><author><style face="normal" font="default" size="100%">Chu, Tzu-Ming</style></author><author><style face="normal" font="default" size="100%">Goodsaid, Federico M</style></author><author><style face="normal" font="default" size="100%">Pusztai, Lajos</style></author><author><style face="normal" font="default" size="100%">Shaughnessy, John D</style></author><author><style face="normal" font="default" size="100%">Oberthuer, André</style></author><author><style face="normal" font="default" size="100%">Thomas, Russell S</style></author><author><style face="normal" font="default" size="100%">Paules, Richard S</style></author><author><style face="normal" font="default" size="100%">Fielden, Mark</style></author><author><style face="normal" font="default" size="100%">Barlogie, Bart</style></author><author><style face="normal" font="default" size="100%">Chen, Weijie</style></author><author><style face="normal" font="default" size="100%">Du, Pan</style></author><author><style face="normal" font="default" size="100%">Fischer, Matthias</style></author><author><style face="normal" font="default" size="100%">Furlanello, Cesare</style></author><author><style face="normal" font="default" size="100%">Gallas, Brandon D</style></author><author><style face="normal" font="default" size="100%">Ge, Xijin</style></author><author><style face="normal" font="default" size="100%">Megherbi, Dalila B</style></author><author><style face="normal" font="default" size="100%">Symmans, W Fraser</style></author><author><style face="normal" font="default" size="100%">Wang, May D</style></author><author><style face="normal" font="default" size="100%">Zhang, John</style></author><author><style face="normal" font="default" size="100%">Bitter, Hans</style></author><author><style face="normal" font="default" size="100%">Brors, Benedikt</style></author><author><style face="normal" font="default" size="100%">Bushel, Pierre R</style></author><author><style face="normal" font="default" size="100%">Bylesjo, Max</style></author><author><style face="normal" font="default" size="100%">Chen, Minjun</style></author><author><style face="normal" font="default" size="100%">Cheng, Jie</style></author><author><style face="normal" font="default" size="100%">Cheng, Jing</style></author><author><style face="normal" font="default" size="100%">Chou, Jeff</style></author><author><style face="normal" font="default" size="100%">Davison, Timothy S</style></author><author><style face="normal" font="default" size="100%">Delorenzi, Mauro</style></author><author><style face="normal" font="default" size="100%">Deng, Youping</style></author><author><style face="normal" font="default" size="100%">Devanarayan, Viswanath</style></author><author><style face="normal" font="default" size="100%">Dix, David J</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Dorff, Kevin C</style></author><author><style face="normal" font="default" size="100%">Elloumi, Fathi</style></author><author><style face="normal" font="default" size="100%">Fan, Jianqing</style></author><author><style face="normal" font="default" size="100%">Fan, Shicai</style></author><author><style face="normal" font="default" size="100%">Fan, Xiaohui</style></author><author><style face="normal" font="default" size="100%">Fang, Hong</style></author><author><style face="normal" font="default" size="100%">Gonzaludo, Nina</style></author><author><style face="normal" font="default" size="100%">Hess, Kenneth R</style></author><author><style face="normal" font="default" size="100%">Hong, Huixiao</style></author><author><style face="normal" font="default" size="100%">Huan, Jun</style></author><author><style face="normal" font="default" size="100%">Irizarry, Rafael A</style></author><author><style face="normal" font="default" size="100%">Judson, Richard</style></author><author><style face="normal" font="default" size="100%">Juraeva, Dilafruz</style></author><author><style face="normal" font="default" size="100%">Lababidi, Samir</style></author><author><style face="normal" font="default" size="100%">Lambert, Christophe G</style></author><author><style face="normal" font="default" size="100%">Li, Li</style></author><author><style face="normal" font="default" size="100%">Li, Yanen</style></author><author><style face="normal" font="default" size="100%">Li, Zhen</style></author><author><style face="normal" font="default" size="100%">Lin, Simon M</style></author><author><style face="normal" font="default" size="100%">Liu, Guozhen</style></author><author><style face="normal" font="default" size="100%">Lobenhofer, Edward K</style></author><author><style face="normal" font="default" size="100%">Luo, Jun</style></author><author><style face="normal" font="default" size="100%">Luo, Wen</style></author><author><style face="normal" font="default" size="100%">McCall, Matthew N</style></author><author><style face="normal" font="default" size="100%">Nikolsky, Yuri</style></author><author><style face="normal" font="default" size="100%">Pennello, Gene A</style></author><author><style face="normal" font="default" size="100%">Perkins, Roger G</style></author><author><style face="normal" font="default" size="100%">Philip, Reena</style></author><author><style face="normal" font="default" size="100%">Popovici, Vlad</style></author><author><style face="normal" font="default" size="100%">Price, Nathan D</style></author><author><style face="normal" font="default" size="100%">Qian, Feng</style></author><author><style face="normal" font="default" size="100%">Scherer, Andreas</style></author><author><style face="normal" font="default" size="100%">Shi, Tieliu</style></author><author><style face="normal" font="default" size="100%">Shi, Weiwei</style></author><author><style face="normal" font="default" size="100%">Sung, Jaeyun</style></author><author><style face="normal" font="default" size="100%">Thierry-Mieg, Danielle</style></author><author><style face="normal" font="default" size="100%">Thierry-Mieg, Jean</style></author><author><style face="normal" font="default" size="100%">Thodima, Venkata</style></author><author><style face="normal" font="default" size="100%">Trygg, Johan</style></author><author><style face="normal" font="default" size="100%">Vishnuvajjala, Lakshmi</style></author><author><style face="normal" font="default" size="100%">Wang, Sue Jane</style></author><author><style face="normal" font="default" size="100%">Wu, Jianping</style></author><author><style face="normal" font="default" size="100%">Wu, Yichao</style></author><author><style face="normal" font="default" size="100%">Xie, Qian</style></author><author><style face="normal" font="default" size="100%">Yousef, Waleed A</style></author><author><style face="normal" font="default" size="100%">Zhang, Liang</style></author><author><style face="normal" font="default" size="100%">Zhang, Xuegong</style></author><author><style face="normal" font="default" size="100%">Zhong, Sheng</style></author><author><style face="normal" font="default" size="100%">Zhou, Yiming</style></author><author><style face="normal" font="default" size="100%">Zhu, Sheng</style></author><author><style face="normal" font="default" size="100%">Arasappan, Dhivya</style></author><author><style face="normal" font="default" size="100%">Bao, Wenjun</style></author><author><style face="normal" font="default" size="100%">Lucas, Anne Bergstrom</style></author><author><style face="normal" font="default" size="100%">Berthold, Frank</style></author><author><style face="normal" font="default" size="100%">Brennan, Richard J</style></author><author><style face="normal" font="default" size="100%">Buness, Andreas</style></author><author><style face="normal" font="default" size="100%">Catalano, Jennifer G</style></author><author><style face="normal" font="default" size="100%">Chang, Chang</style></author><author><style face="normal" font="default" size="100%">Chen, Rong</style></author><author><style face="normal" font="default" size="100%">Cheng, Yiyu</style></author><author><style face="normal" font="default" size="100%">Cui, Jian</style></author><author><style face="normal" font="default" size="100%">Czika, Wendy</style></author><author><style face="normal" font="default" size="100%">Demichelis, Francesca</style></author><author><style face="normal" font="default" size="100%">Deng, Xutao</style></author><author><style face="normal" font="default" size="100%">Dosymbekov, Damir</style></author><author><style face="normal" font="default" size="100%">Eils, Roland</style></author><author><style face="normal" font="default" size="100%">Feng, Yang</style></author><author><style face="normal" font="default" size="100%">Fostel, Jennifer</style></author><author><style face="normal" font="default" size="100%">Fulmer-Smentek, Stephanie</style></author><author><style face="normal" font="default" size="100%">Fuscoe, James C</style></author><author><style face="normal" font="default" size="100%">Gatto, Laurent</style></author><author><style face="normal" font="default" size="100%">Ge, Weigong</style></author><author><style face="normal" font="default" size="100%">Goldstein, Darlene R</style></author><author><style face="normal" font="default" size="100%">Guo, Li</style></author><author><style face="normal" font="default" size="100%">Halbert, Donald N</style></author><author><style face="normal" font="default" size="100%">Han, Jing</style></author><author><style face="normal" font="default" size="100%">Harris, Stephen C</style></author><author><style face="normal" font="default" size="100%">Hatzis, Christos</style></author><author><style face="normal" font="default" size="100%">Herman, Damir</style></author><author><style face="normal" font="default" size="100%">Huang, Jianping</style></author><author><style face="normal" font="default" size="100%">Jensen, Roderick V</style></author><author><style face="normal" font="default" size="100%">Jiang, Rui</style></author><author><style face="normal" font="default" size="100%">Johnson, Charles D</style></author><author><style face="normal" font="default" size="100%">Jurman, Giuseppe</style></author><author><style face="normal" font="default" size="100%">Kahlert, Yvonne</style></author><author><style face="normal" font="default" size="100%">Khuder, Sadik A</style></author><author><style face="normal" font="default" size="100%">Kohl, Matthias</style></author><author><style face="normal" font="default" size="100%">Li, Jianying</style></author><author><style face="normal" font="default" size="100%">Li, Li</style></author><author><style face="normal" font="default" size="100%">Li, Menglong</style></author><author><style face="normal" font="default" size="100%">Li, Quan-Zhen</style></author><author><style face="normal" font="default" size="100%">Li, Shao</style></author><author><style face="normal" font="default" size="100%">Li, Zhiguang</style></author><author><style face="normal" font="default" size="100%">Liu, Jie</style></author><author><style face="normal" font="default" size="100%">Liu, Ying</style></author><author><style face="normal" font="default" size="100%">Liu, Zhichao</style></author><author><style face="normal" font="default" size="100%">Meng, Lu</style></author><author><style face="normal" font="default" size="100%">Madera, Manuel</style></author><author><style face="normal" font="default" size="100%">Martinez-Murillo, Francisco</style></author><author><style face="normal" font="default" size="100%">Medina, Ignacio</style></author><author><style face="normal" font="default" size="100%">Meehan, Joseph</style></author><author><style face="normal" font="default" size="100%">Miclaus, Kelci</style></author><author><style face="normal" font="default" size="100%">Moffitt, Richard A</style></author><author><style face="normal" font="default" size="100%">Montaner, David</style></author><author><style face="normal" font="default" size="100%">Mukherjee, Piali</style></author><author><style face="normal" font="default" size="100%">Mulligan, George J</style></author><author><style face="normal" font="default" size="100%">Neville, Padraic</style></author><author><style face="normal" font="default" size="100%">Nikolskaya, Tatiana</style></author><author><style face="normal" font="default" size="100%">Ning, Baitang</style></author><author><style face="normal" font="default" size="100%">Page, Grier P</style></author><author><style face="normal" font="default" size="100%">Parker, Joel</style></author><author><style face="normal" font="default" size="100%">Parry, R Mitchell</style></author><author><style face="normal" font="default" size="100%">Peng, Xuejun</style></author><author><style face="normal" font="default" size="100%">Peterson, Ron L</style></author><author><style face="normal" font="default" size="100%">Phan, John H</style></author><author><style face="normal" font="default" size="100%">Quanz, Brian</style></author><author><style face="normal" font="default" size="100%">Ren, Yi</style></author><author><style face="normal" font="default" size="100%">Riccadonna, Samantha</style></author><author><style face="normal" font="default" size="100%">Roter, Alan H</style></author><author><style face="normal" font="default" size="100%">Samuelson, Frank W</style></author><author><style face="normal" font="default" size="100%">Schumacher, Martin M</style></author><author><style face="normal" font="default" size="100%">Shambaugh, Joseph D</style></author><author><style face="normal" font="default" size="100%">Shi, Qiang</style></author><author><style face="normal" font="default" size="100%">Shippy, Richard</style></author><author><style face="normal" font="default" size="100%">Si, Shengzhu</style></author><author><style face="normal" font="default" size="100%">Smalter, Aaron</style></author><author><style face="normal" font="default" size="100%">Sotiriou, Christos</style></author><author><style face="normal" font="default" size="100%">Soukup, Mat</style></author><author><style face="normal" font="default" size="100%">Staedtler, Frank</style></author><author><style face="normal" font="default" size="100%">Steiner, Guido</style></author><author><style face="normal" font="default" size="100%">Stokes, Todd H</style></author><author><style face="normal" font="default" size="100%">Sun, Qinglan</style></author><author><style face="normal" font="default" size="100%">Tan, Pei-Yi</style></author><author><style face="normal" font="default" size="100%">Tang, Rong</style></author><author><style face="normal" font="default" size="100%">Tezak, Zivana</style></author><author><style face="normal" font="default" size="100%">Thorn, Brett</style></author><author><style face="normal" font="default" size="100%">Tsyganova, Marina</style></author><author><style face="normal" font="default" size="100%">Turpaz, Yaron</style></author><author><style face="normal" font="default" size="100%">Vega, Silvia C</style></author><author><style face="normal" font="default" size="100%">Visintainer, Roberto</style></author><author><style face="normal" font="default" size="100%">von Frese, Juergen</style></author><author><style face="normal" font="default" size="100%">Wang, Charles</style></author><author><style face="normal" font="default" size="100%">Wang, Eric</style></author><author><style face="normal" font="default" size="100%">Wang, Junwei</style></author><author><style face="normal" font="default" size="100%">Wang, Wei</style></author><author><style face="normal" font="default" size="100%">Westermann, Frank</style></author><author><style face="normal" font="default" size="100%">Willey, James C</style></author><author><style face="normal" font="default" size="100%">Woods, Matthew</style></author><author><style face="normal" font="default" size="100%">Wu, Shujian</style></author><author><style face="normal" font="default" size="100%">Xiao, Nianqing</style></author><author><style face="normal" font="default" size="100%">Xu, Joshua</style></author><author><style face="normal" font="default" size="100%">Xu, Lei</style></author><author><style face="normal" font="default" size="100%">Yang, Lun</style></author><author><style face="normal" font="default" size="100%">Zeng, Xiao</style></author><author><style face="normal" font="default" size="100%">Zhang, Jialu</style></author><author><style face="normal" font="default" size="100%">Zhang, Li</style></author><author><style face="normal" font="default" size="100%">Zhang, Min</style></author><author><style face="normal" font="default" size="100%">Zhao, Chen</style></author><author><style face="normal" font="default" size="100%">Puri, Raj K</style></author><author><style face="normal" font="default" size="100%">Scherf, Uwe</style></author><author><style face="normal" font="default" size="100%">Tong, Weida</style></author><author><style face="normal" font="default" size="100%">Wolfinger, Russell D</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.</style></title><secondary-title><style face="normal" font="default" size="100%">Nature biotechnology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2010 Aug</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.nature.com/nbt/journal/v28/n8/full/nbt.1665.html</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">28</style></volume><pages><style face="normal" font="default" size="100%">827-38</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, &amp;gt;30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Montaner, David</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multidimensional gene set analysis of genomic data.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS One</style></secondary-title><alt-title><style face="normal" font="default" size="100%">PLoS One</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Databases, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Regulatory Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Statistical</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2010 Apr 27</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">e10348</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Understanding the functional implications of changes in gene expression, mutations, etc., is the aim of most genomic experiments. To achieve this, several functional profiling methods have been proposed. Such methods study the behaviour of different gene modules (e.g. gene ontology terms) in response to one particular variable (e.g. differential gene expression). In spite to the wealth of information provided by functional profiling methods, a common limitation to all of them is their inherent unidimensional nature. In order to overcome this restriction we present a multidimensional logistic model that allows studying the relationship of gene modules with different genome-scale measurements (e.g. differential expression, genotyping association, methylation, copy number alterations, heterozygosity, etc.) simultaneously. Moreover, the relationship of such functional modules with the interactions among the variables can also be studied, which produces novel results impossible to be derived from the conventional unidimensional functional profiling methods. We report sound results of gene sets associations that remained undetected by the conventional one-dimensional gene set analysis in several examples. Our findings demonstrate the potential of the proposed approach for the discovery of new cell functionalities with complex dependences on more than one variable.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/20436964?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Barragán, Isabel</style></author><author><style face="normal" font="default" size="100%">Borrego, Salud</style></author><author><style face="normal" font="default" size="100%">Pieras, Juan Ignacio</style></author><author><style face="normal" font="default" size="100%">González-del Pozo, María</style></author><author><style face="normal" font="default" size="100%">Santoyo, Javier</style></author><author><style face="normal" font="default" size="100%">Ayuso, Carmen</style></author><author><style face="normal" font="default" size="100%">Baiget, Montserrat</style></author><author><style face="normal" font="default" size="100%">Millán, José M</style></author><author><style face="normal" font="default" size="100%">Mena, Marcela</style></author><author><style face="normal" font="default" size="100%">Abd El-Aziz, Mai M</style></author><author><style face="normal" font="default" size="100%">Audo, Isabelle</style></author><author><style face="normal" font="default" size="100%">Zeitz, Christina</style></author><author><style face="normal" font="default" size="100%">Littink, Karin W</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Bhattacharya, Shomi S</style></author><author><style face="normal" font="default" size="100%">Antiňolo, Guillermo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mutation spectrum of EYS in Spanish patients with autosomal recessive retinitis pigmentosa.</style></title><secondary-title><style face="normal" font="default" size="100%">Hum Mutat</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Hum Mutat</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amino Acid Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Case-Control Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Mutational Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Drosophila Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Evolution, Molecular</style></keyword><keyword><style  face="normal" font="default" size="100%">Eye Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Genes, Recessive</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Sequence Data</style></keyword><keyword><style  face="normal" font="default" size="100%">mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Pedigree</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Structure, Tertiary</style></keyword><keyword><style  face="normal" font="default" size="100%">Retinitis pigmentosa</style></keyword><keyword><style  face="normal" font="default" size="100%">Spain</style></keyword><keyword><style  face="normal" font="default" size="100%">Structural Homology, Protein</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2010 Nov</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">31</style></volume><pages><style face="normal" font="default" size="100%">E1772-800</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Retinitis pigmentosa (RP) is a heterogeneous group of inherited retinal dystrophies characterised ultimately by the loss of photoreceptor cells. We have recently identified a new gene(EYS) encoding an ortholog of Drosophila space maker (spam) as a commonly mutated gene in autosomal recessive RP. In the present study, we report the identification of 73 sequence variations in EYS, of which 28 are novel. Of these, 42.9% (12/28) are very likely pathogenic, 17.9% (5/28)are possibly pathogenic, whereas 39.3% (11/28) are SNPs. In addition, we have detected 3 pathogenic changes previously reported in other populations. We are also presenting the characterisation of EYS homologues in different species, and a detailed analysis of the EYS domains, with the identification of an interesting novel feature: a putative coiled-coil domain.Majority of the mutations in the arRP patients have been found within the domain structures of EYS. The minimum observed prevalence of distinct EYS mutations in our group of patients is of 15.9% (15/94), confirming a major involvement of EYS in the pathogenesis of arRP in the Spanish population. Along with the detection of three recurrent mutations in Caucasian population, our hypothesis of EYS being the first prevalent gene in arRP has been reinforced in the present study.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">11</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/21069908?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>6</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mateos, Alvaro</style></author><author><style face="normal" font="default" size="100%">Herrero, Javier</style></author><author><style face="normal" font="default" size="100%">Tamames, Javier</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Lin, Simon M.</style></author><author><style face="normal" font="default" size="100%">Johnson, Kimberly F.</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Methods of Microarray Data Analysis IISupervised Neural Networks for Clustering Conditions in DNA Array Data After Reducing Noise by Clustering Gene Expression Profiles</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.springerlink.com/index/10.1007/b112982http://link.springer.com/10.1007/0-306-47598-7_7http://www.springerlink.com/index/pdf/10.1007/0-306-47598-7_7</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Kluwer Academic Publishers</style></publisher><pub-location><style face="normal" font="default" size="100%">Boston</style></pub-location><pages><style face="normal" font="default" size="100%">91 - 103</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record></records></xml>