<?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%">Bogliolo, Massimo</style></author><author><style face="normal" font="default" size="100%">Pujol, Roser</style></author><author><style face="normal" font="default" size="100%">Aza-Carmona, Miriam</style></author><author><style face="normal" font="default" size="100%">Muñoz-Subirana, Núria</style></author><author><style face="normal" font="default" size="100%">Rodriguez-Santiago, Benjamin</style></author><author><style face="normal" font="default" size="100%">Casado, José Antonio</style></author><author><style face="normal" font="default" size="100%">Rio, Paula</style></author><author><style face="normal" font="default" size="100%">Bauser, Christopher</style></author><author><style face="normal" font="default" size="100%">Reina-Castillón, Judith</style></author><author><style face="normal" font="default" size="100%">Lopez-Sanchez, Marcos</style></author><author><style face="normal" font="default" size="100%">Gonzalez-Quereda, Lidia</style></author><author><style face="normal" font="default" size="100%">Gallano, Pia</style></author><author><style face="normal" font="default" size="100%">Catalá, Albert</style></author><author><style face="normal" font="default" size="100%">Ruiz-Llobet, Ana</style></author><author><style face="normal" font="default" size="100%">Badell, Isabel</style></author><author><style face="normal" font="default" size="100%">Diaz-Heredia, Cristina</style></author><author><style face="normal" font="default" size="100%">Hladun, Raquel</style></author><author><style face="normal" font="default" size="100%">Senent, Leonort</style></author><author><style face="normal" font="default" size="100%">Argiles, Bienvenida</style></author><author><style face="normal" font="default" size="100%">Bergua Burgues, Juan Miguel</style></author><author><style face="normal" font="default" size="100%">Bañez, Fatima</style></author><author><style face="normal" font="default" size="100%">Arrizabalaga, Beatriz</style></author><author><style face="normal" font="default" size="100%">López Almaraz, Ricardo</style></author><author><style face="normal" font="default" size="100%">Lopez, Monica</style></author><author><style face="normal" font="default" size="100%">Figuera, Ángela</style></author><author><style face="normal" font="default" size="100%">Molinés, Antonio</style></author><author><style face="normal" font="default" size="100%">Pérez de Soto, Inmaculada</style></author><author><style face="normal" font="default" size="100%">Hernando, Inés</style></author><author><style face="normal" font="default" size="100%">Muñoz, Juan Antonio</style></author><author><style face="normal" font="default" size="100%">Del Rosario Marin, Maria</style></author><author><style face="normal" font="default" size="100%">Balmaña, Judith</style></author><author><style face="normal" font="default" size="100%">Stjepanovic, Neda</style></author><author><style face="normal" font="default" size="100%">Carrasco, Estela</style></author><author><style face="normal" font="default" size="100%">Cuesta, Isabel</style></author><author><style face="normal" font="default" size="100%">Cosuelo, José Miguel</style></author><author><style face="normal" font="default" size="100%">Regueiro, Alexandra</style></author><author><style face="normal" font="default" size="100%">Moraleda Jimenez, José</style></author><author><style face="normal" font="default" size="100%">Galera-Miñarro, Ana Maria</style></author><author><style face="normal" font="default" size="100%">Rosiñol, Laura</style></author><author><style face="normal" font="default" size="100%">Carrió, Anna</style></author><author><style face="normal" font="default" size="100%">Beléndez-Bieler, Cristina</style></author><author><style face="normal" font="default" size="100%">Escudero Soto, Antonio</style></author><author><style face="normal" font="default" size="100%">Cela, Elena</style></author><author><style face="normal" font="default" size="100%">de la Mata, Gregorio</style></author><author><style face="normal" font="default" size="100%">Fernández-Delgado, Rafael</style></author><author><style face="normal" font="default" size="100%">Garcia-Pardos, Maria Carmen</style></author><author><style face="normal" font="default" size="100%">Sáez-Villaverde, Raquel</style></author><author><style face="normal" font="default" size="100%">Barragaño, Marta</style></author><author><style face="normal" font="default" size="100%">Portugal, Raquel</style></author><author><style face="normal" font="default" size="100%">Lendinez, Francisco</style></author><author><style face="normal" font="default" size="100%">Hernadez, Ines</style></author><author><style face="normal" font="default" size="100%">Vagace, José Manue</style></author><author><style face="normal" font="default" size="100%">Tapia, Maria</style></author><author><style face="normal" font="default" size="100%">Nieto, José</style></author><author><style face="normal" font="default" size="100%">Garcia, Marta</style></author><author><style face="normal" font="default" size="100%">Gonzalez, Macarena</style></author><author><style face="normal" font="default" size="100%">Vicho, Cristina</style></author><author><style face="normal" font="default" size="100%">Galvez, Eva</style></author><author><style face="normal" font="default" size="100%">Valiente, Alberto</style></author><author><style face="normal" font="default" size="100%">Antelo, Maria Luisa</style></author><author><style face="normal" font="default" size="100%">Ancliff, Phil</style></author><author><style face="normal" font="default" size="100%">García, Francisco</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Sevilla, Julian</style></author><author><style face="normal" font="default" size="100%">Paprotka, Tobias</style></author><author><style face="normal" font="default" size="100%">Pérez-Jurado, Luis Alberto</style></author><author><style face="normal" font="default" size="100%">Bueren, Juan</style></author><author><style face="normal" font="default" size="100%">Surralles, Jordi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Optimised molecular genetic diagnostics of Fanconi anaemia by whole exome sequencing and functional studies.</style></title><secondary-title><style face="normal" font="default" size="100%">J Med Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J Med Genet</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Cell Line</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Copy Number Variations</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Repair</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA-Binding Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Fanconi Anemia</style></keyword><keyword><style  face="normal" font="default" size="100%">Fanconi Anemia Complementation Group A Protein</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Knockout Techniques</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Predisposition to Disease</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%">Mutation, Missense</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">whole exome sequencing</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 04</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">57</style></volume><pages><style face="normal" font="default" size="100%">258-268</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;PURPOSE: &lt;/b&gt;Patients with Fanconi anaemia (FA), a rare DNA repair genetic disease, exhibit chromosome fragility, bone marrow failure, malformations and cancer susceptibility. FA molecular diagnosis is challenging since FA is caused by point mutations and large deletions in 22 genes following three heritability patterns. To optimise FA patients' characterisation, we developed a simplified but effective methodology based on whole exome sequencing (WES) and functional studies.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;68 patients with FA were analysed by commercial WES services. Copy number variations were evaluated by sequencing data analysis with RStudio. To test  missense variants, wt FANCA cDNA was cloned and variants were introduced by site-directed mutagenesis. Vectors were then tested for their ability to complement DNA repair defects of a FANCA-KO human cell line generated by TALEN technologies.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;We identified 93.3% of mutated alleles including large deletions. We determined the pathogenicity of three FANCA missense variants and demonstrated that two  variants reported in mutations databases as 'affecting functions' are SNPs. Deep analysis of sequencing data revealed patients' true mutations, highlighting the importance of functional analysis. In one patient, no pathogenic variant could be identified in any of the 22 known FA genes, and in seven patients, only one deleterious variant could be identified (three patients each with FANCA and FANCD2 and one patient with FANCE mutations) CONCLUSION: WES and proper bioinformatics analysis are sufficient to effectively characterise patients with FA regardless of the rarity of their complementation group, type of mutations, mosaic condition and DNA source.&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/31586946?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%">Esteban-Medina, Marina</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%">Dopazo, Joaquin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Exploring the druggable space around the Fanconi anemia pathway using machine learning and mechanistic models.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Bioinformatics</style></secondary-title><alt-title><style face="normal" font="default" size="100%">BMC Bioinformatics</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Databases, Factual</style></keyword><keyword><style  face="normal" font="default" size="100%">Fanconi Anemia</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%">Machine Learning</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal Transduction</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2019 Jul 02</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">20</style></volume><pages><style face="normal" font="default" size="100%">370</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;In spite of the abundance of genomic data, predictive models that describe phenotypes as a function of gene expression or mutations are difficult to obtain because they are affected by the curse of dimensionality, given the disbalance between samples and candidate genes. And this is especially dramatic in scenarios in which the availability of samples is difficult, such as the case of rare diseases.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;The application of multi-output regression machine learning methodologies to predict the potential effect of external proteins over the signaling circuits that trigger Fanconi anemia related cell functionalities, inferred with a mechanistic model, allowed us to detect over 20 potential therapeutic targets.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;The use of artificial intelligence methods for the prediction of potentially causal relationships between proteins of interest and cell activities related with disease-related phenotypes opens promising avenues for the systematic search of new targets in rare diseases.&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/31266445?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%">García-Alonso, Luz</style></author><author><style face="normal" font="default" size="100%">Alonso, Roberto</style></author><author><style face="normal" font="default" size="100%">Vidal, Enrique</style></author><author><style face="normal" font="default" size="100%">Amadoz, Alicia</style></author><author><style face="normal" font="default" size="100%">De Maria, Alejandro</style></author><author><style face="normal" font="default" size="100%">Minguez, Pablo</style></author><author><style face="normal" font="default" size="100%">Medina, Ignacio</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%">Discovering the hidden sub-network component in a ranked list of genes or proteins derived from genomic experiments.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Bipolar Disorder</style></keyword><keyword><style  face="normal" font="default" size="100%">Fanconi Anemia</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Regulatory Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">Genes, Neoplasm</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome-Wide Association Study</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%">Protein Interaction Mapping</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 Nov 01</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">40</style></volume><pages><style face="normal" font="default" size="100%">e158</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Genomic experiments (e.g. differential gene expression, single-nucleotide polymorphism association) typically produce ranked list of genes. We present a simple but powerful approach which uses protein-protein interaction data to detect sub-networks within such ranked lists of genes or proteins. We performed an exhaustive study of network parameters that allowed us concluding that the average number of components and the average number of nodes per component are the parameters that best discriminate between real and random networks. A novel aspect that increases the efficiency of this strategy in finding sub-networks is that, in addition to direct connections, also connections mediated by intermediate nodes are considered to build up the sub-networks. The possibility of using of such intermediate nodes makes this approach more robust to noise. It also overcomes some limitations intrinsic to experimental designs based on differential expression, in which some nodes are invariant across conditions. The proposed approach can also be used for candidate disease-gene prioritization. Here, we demonstrate the usefulness of the approach by means of several case examples that include a differential expression analysis in Fanconi Anemia, a genome-wide association study of bipolar disorder and a genome-scale study of essentiality in cancer genes. An efficient and easy-to-use web interface (available at http://www.babelomics.org) based on HTML5 technologies is also provided to run the algorithm and represent the network.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">20</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/22844098?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%">Bleda, Marta</style></author><author><style face="normal" font="default" size="100%">Medina, Ignacio</style></author><author><style face="normal" font="default" size="100%">Alonso, Roberto</style></author><author><style face="normal" font="default" size="100%">De Maria, Alejandro</style></author><author><style face="normal" font="default" size="100%">Salavert, Francisco</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%">Inferring the regulatory network behind a gene expression experiment.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Binding Sites</style></keyword><keyword><style  face="normal" font="default" size="100%">Databases, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Fanconi Anemia</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Regulatory Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">MicroRNAs</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcriptome</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 Jul</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">40</style></volume><pages><style face="normal" font="default" size="100%">W168-72</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Transcription factors (TFs) and miRNAs are the most important dynamic regulators in the control of gene expression in multicellular organisms. These regulatory elements play crucial roles in development, cell cycling and cell signaling, and they have also been associated with many diseases. The Regulatory Network Analysis Tool (RENATO) web server makes the exploration of regulatory networks easy, enabling a better understanding of functional modularity and network integrity under specific perturbations. RENATO is suitable for the analysis of the result of expression profiling experiments. The program analyses lists of genes and search for the regulators compatible with its activation or deactivation. Tests of single enrichment or gene set enrichment allow the selection of the subset of TFs or miRNAs significantly involved in the regulation of the query genes. RENATO also offers an interactive advanced graphical interface that allows exploring the regulatory network found.RENATO is available at: http://renato.bioinfo.cipf.es/.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">Web Server issue</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/22693210?dopt=Abstract</style></custom1></record></records></xml>