@article {794, title = {Case report: Analysis of phage therapy failure in a patient with a Pseudomonas aeruginosa prosthetic vascular graft infection}, journal = {Front Med (Lausanne)}, volume = {10}, year = {2023}, month = {2023}, pages = {1199657}, abstract = {

Clinical case of a patient with a multidrug-resistant prosthetic vascular graft infection which was treated with a cocktail of phages (PT07, 14/01, and PNM) in combination with ceftazidime-avibactam (CZA). After the application of the phage treatment and in absence of antimicrobial therapy, a new bloodstream infection (BSI) with a septic residual limb metastasis occurred, now involving a wild-type strain being susceptible to {\ss}-lactams and quinolones. Clinical strains were analyzed by microbiology and whole genome sequencing techniques. In relation with phage administration, the clinical isolates of before phage therapy (HE2011471) and post phage therapy (HE2105886) showed a clonal relationship but with important genomic changes which could be involved in the resistance to this therapy. Finally, phenotypic studies showed a decrease in Minimum Inhibitory Concentration (MIC) to {\ss}-lactams and quinolones as well as an increase of the biofilm production and phage resistant mutants in the clinical isolate of post phage therapy.

}, doi = {10.3389/fmed.2023.1199657}, url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10235614/}, author = {Blasco, Lucia and L{\'o}pez-Hern{\'a}ndez, Inmaculada and Rodr{\'\i}guez-Fern{\'a}ndez, Miguel and Perez-Florido, Javier and Casimiro-Soriguer, Carlos S} } @book {798, title = {Cell-Level Pathway Scoring Comparison with~a~Biologically Constrained Variational Autoencoder}, series = {Lecture Notes in Computer Science. Computational Methods in Systems Biology}, volume = {14137}, year = {2023}, pages = {62 - 77}, publisher = {Springer Nature Switzerland}, organization = {Springer Nature Switzerland}, address = {Cham}, isbn = {978-3-031-42696-4}, issn = {0302-9743}, doi = {10.1007/978-3-031-42697-110.1007/978-3-031-42697-1_5}, url = {https://link.springer.com/chapter/10.1007/978-3-031-42697-1_5}, author = {Gundogdu, Pelin and Pay{\'a}-Milans, Miriam and Alamo-Alvarez, Inmaculada and Nepomuceno-Chamorro, Isabel A. and Dopazo, Joaquin and Loucera, Carlos} } @article {770, title = {A Comprehensive Analysis of 21 Actionable Pharmacogenes in the Spanish Population: From Genetic Characterisation to Clinical Impact.}, journal = {Pharmaceutics}, volume = {15}, year = {2023}, month = {2023 Apr 19}, abstract = {

The implementation of pharmacogenetics (PGx) is a main milestones of precision medicine nowadays in order to achieve safer and more effective therapies. Nevertheless, the implementation of PGx diagnostics is extremely slow and unequal worldwide, in part due to a lack of ethnic PGx information. We analysed genetic data from 3006 Spanish individuals obtained by different high-throughput (HT) techniques. Allele frequencies were determined in our population for the main 21 actionable PGx genes associated with therapeutical changes. We found that 98\% of the Spanish population harbours at least one allele associated with a therapeutical change and, thus, there would be a need for a therapeutical change in a mean of 3.31 of the 64 associated drugs. We also identified 326 putative deleterious variants that were not previously related with PGx in 18 out of the 21 main PGx genes evaluated and a total of 7122 putative deleterious variants for the 1045 PGx genes described. Additionally, we performed a comparison of the main HT diagnostic techniques, revealing that after whole genome sequencing, genotyping with the PGx HT array is the most suitable solution for PGx diagnostics. Finally, all this information was integrated in the Collaborative Spanish Variant Server to be available to and updated by the scientific community.

}, issn = {1999-4923}, doi = {10.3390/pharmaceutics15041286}, author = {N{\'u}{\~n}ez-Torres, Roc{\'\i}o and Pita, Guillermo and Pe{\~n}a-Chilet, Maria and L{\'o}pez-L{\'o}pez, Daniel and Zamora, Jorge and Rold{\'a}n, Gema and Herr{\'a}ez, Bel{\'e}n and Alvarez, Nuria and Alonso, Mar{\'\i}a Rosario and Dopazo, Joaquin and Gonz{\'a}lez-Neira, Anna} } @article {771, title = {Crosstalk between Metabolite Production and Signaling Activity in Breast Cancer.}, journal = {Int J Mol Sci}, volume = {24}, year = {2023}, month = {2023 Apr 18}, abstract = {

The reprogramming of metabolism is a recognized cancer hallmark. It is well known that different signaling pathways regulate and orchestrate this reprogramming that contributes to cancer initiation and development. However, recent evidence is accumulating, suggesting that several metabolites could play a relevant role in regulating signaling pathways. To assess the potential role of metabolites in the regulation of signaling pathways, both metabolic and signaling pathway activities of Breast invasive Carcinoma (BRCA) have been modeled using mechanistic models. Gaussian Processes, powerful machine learning methods, were used in combination with SHapley Additive exPlanations (SHAP), a recent methodology that conveys causality, to obtain potential causal relationships between the production of metabolites and the regulation of signaling pathways. A total of 317 metabolites were found to have a strong impact on signaling circuits. The results presented here point to the existence of a complex crosstalk between signaling and metabolic pathways more complex than previously was thought.

}, issn = {1422-0067}, doi = {10.3390/ijms24087450}, author = {Cubuk, Cankut and Loucera, Carlos and Pe{\~n}a-Chilet, Maria and Dopazo, Joaquin} } @article {769, title = {A crowdsourcing database for the copy-number variation of the Spanish population.}, journal = {Hum Genomics}, volume = {17}, year = {2023}, month = {2023 Mar 09}, pages = {20}, abstract = {

BACKGROUND: Despite being a very common type of genetic variation, the distribution of copy-number variations (CNVs) in the population is still poorly understood. The knowledge of the genetic variability, especially at the level of the local population, is a critical factor for distinguishing pathogenic from non-pathogenic variation in the discovery of new disease variants.

RESULTS: Here, we present the SPAnish Copy Number Alterations Collaborative Server (SPACNACS), which currently contains copy number variation profiles obtained from more than 400 genomes and exomes of unrelated Spanish individuals. By means of a collaborative crowdsourcing effort whole genome and whole exome sequencing data, produced by local genomic projects and for other purposes, is continuously collected. Once checked both, the Spanish ancestry and the lack of kinship with other individuals in the SPACNACS, the CNVs are inferred for these sequences and they are used to populate the database. A web interface allows querying the database with different filters that include ICD10 upper categories. This allows discarding samples from the disease under study and obtaining pseudo-control CNV profiles from the local population. We also show here additional studies on the local impact of CNVs in some phenotypes and on pharmacogenomic variants. SPACNACS can be accessed at: http://csvs.clinbioinfosspa.es/spacnacs/ .

CONCLUSION: SPACNACS facilitates disease gene discovery by providing detailed information of the local variability of the population and exemplifies how to reuse genomic data produced for other purposes to build a local reference database.

}, issn = {1479-7364}, doi = {10.1186/s40246-023-00466-8}, author = {L{\'o}pez-L{\'o}pez, Daniel and Rold{\'a}n, Gema and Fernandez-Rueda, Jose L and Bostelmann, Gerrit and Carmona, Rosario and Aquino, Virginia and Perez-Florido, Javier and Ortuno, Francisco and Pita, Guillermo and N{\'u}{\~n}ez-Torres, Roc{\'\i}o and Gonz{\'a}lez-Neira, Anna and Pe{\~n}a-Chilet, Maria and Dopazo, Joaquin} } @article {750, title = {CIBERER: Spanish National Network for Research on Rare Diseases: a highly productive collaborative initiative.}, journal = {Clin Genet}, year = {2022}, month = {2022 Jan 20}, abstract = {

CIBER (Center for Biomedical Network Research; Centro de Investigaci{\'o}n Biom{\'e}dica En Red) is a public national consortium created in 2006 under the umbrella of the Spanish National Institute of Health Carlos III (ISCIII). This innovative research structure comprises 11 different specific areas dedicated to the main public health priorities in the National Health System. CIBERER, the thematic area of CIBER focused on Rare Diseases currently consists of 75 research groups belonging to universities, research centers and hospitals of the entire country. CIBERER{\textquoteright}s mission is to be a center prioritizing and favoring collaboration and cooperation between biomedical and clinical research groups, with special emphasis on the aspects of genetic, molecular, biochemical and cellular research of rare diseases. This research is the basis for providing new tools for the diagnosis and therapy of low-prevalence diseases, in line with the International Rare Diseases Research Consortium (IRDiRC) objectives, thus favoring translational research between the scientific environment of the laboratory and the clinical setting of health centers. In this paper, we intend to review CIBERER{\textquoteright}s 15-year journey and summarize the main results obtained in terms of internationalization, scientific production, contributions towards the discovery of new therapies and novel genes associated to diseases, cooperation with patients{\textquoteright} associations and many other topics related to rare disease research. This article is protected by copyright. All rights reserved.

}, issn = {1399-0004}, doi = {10.1111/cge.14113}, author = {Luque, Juan and Mendes, Ingrid and G{\'o}mez, Beatriz and Morte, Beatriz and de Heredia, Miguel L{\'o}pez and Herreras, Enrique and Corrochano, Virginia and Bueren, Juan and Gallano, Pia and Artuch, Rafael and Fillat, Cristina and P{\'e}rez-Jurado, Luis A and Montoliu, Lluis and Carracedo, {\'A}ngel and Mill{\'a}n, Jos{\'e} M and Webb, Susan M and Palau, Francesc and Lapunzina, Pablo} } @article {726, title = {A comprehensive database for integrated analysis of omics data in autoimmune diseases.}, journal = {BMC Bioinformatics}, volume = {22}, year = {2021}, month = {2021 Jun 24}, pages = {343}, abstract = {

BACKGROUND: Autoimmune diseases are heterogeneous pathologies with difficult diagnosis and few therapeutic options. In the last decade, several omics studies have provided significant insights into the molecular mechanisms of these diseases. Nevertheless, data from different cohorts and pathologies are stored independently in public repositories and a unified resource is imperative to assist researchers in this field.

RESULTS: Here, we present Autoimmune Diseases Explorer ( https://adex.genyo.es ), a database that integrates 82 curated transcriptomics and methylation studies covering 5609 samples for some of the most common autoimmune diseases. The database provides, in an easy-to-use environment, advanced data analysis and statistical methods for exploring omics datasets, including meta-analysis, differential expression or pathway analysis.

CONCLUSIONS: This is the first omics database focused on autoimmune diseases. This resource incorporates homogeneously processed data to facilitate integrative analyses among studies.

}, keywords = {Autoimmune Diseases, Computational Biology, Databases, Factual, Humans}, issn = {1471-2105}, doi = {10.1186/s12859-021-04268-4}, author = {Martorell-Marug{\'a}n, Jordi and L{\'o}pez-Dom{\'\i}nguez, Ra{\'u}l and Garc{\'\i}a-Moreno, Adri{\'a}n and Toro-Dom{\'\i}nguez, Daniel and Villatoro-Garc{\'\i}a, Juan Antonio and Barturen, Guillermo and Mart{\'\i}n-G{\'o}mez, Adoraci{\'o}n and Troule, Kevin and G{\'o}mez-L{\'o}pez, Gonzalo and Al-Shahrour, F{\'a}tima and Gonz{\'a}lez-Rumayor, V{\'\i}ctor and Pe{\~n}a-Chilet, Maria and Dopazo, Joaquin and Saez-Rodriguez, Julio and Alarc{\'o}n-Riquelme, Marta E and Carmona-S{\'a}ez, Pedro} } @article {736, title = {COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.}, journal = {Mol Syst Biol}, volume = {17}, year = {2021}, month = {2021 10}, pages = {e10387}, abstract = {

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

}, keywords = {Antiviral Agents, Computational Biology, Computer Graphics, COVID-19, Cytokines, Data Mining, Databases, Factual, Gene Expression Regulation, Host Microbial Interactions, Humans, Immunity, Cellular, Immunity, Humoral, Immunity, Innate, Lymphocytes, Metabolic Networks and Pathways, Myeloid Cells, Protein Interaction Mapping, SARS-CoV-2, Signal Transduction, Software, Transcription Factors, Viral Proteins}, issn = {1744-4292}, doi = {10.15252/msb.202110387}, author = {Ostaszewski, Marek and Niarakis, Anna and Mazein, Alexander and Kuperstein, Inna and Phair, Robert and Orta-Resendiz, Aurelio and Singh, Vidisha and Aghamiri, Sara Sadat and Acencio, Marcio Luis and Glaab, Enrico and Ruepp, Andreas and Fobo, Gisela and Montrone, Corinna and Brauner, Barbara and Frishman, Goar and Monraz G{\'o}mez, Luis Crist{\'o}bal and Somers, Julia and Hoch, Matti and Kumar Gupta, Shailendra and Scheel, Julia and Borlinghaus, Hanna and Czauderna, Tobias and Schreiber, Falk and Montagud, Arnau and Ponce de Leon, Miguel and Funahashi, Akira and Hiki, Yusuke and Hiroi, Noriko and Yamada, Takahiro G and Dr{\"a}ger, Andreas and Renz, Alina and Naveez, Muhammad and Bocskei, Zsolt and Messina, Francesco and B{\"o}rnigen, Daniela and Fergusson, Liam and Conti, Marta and Rameil, Marius and Nakonecnij, Vanessa and Vanhoefer, Jakob and Schmiester, Leonard and Wang, Muying and Ackerman, Emily E and Shoemaker, Jason E and Zucker, Jeremy and Oxford, Kristie and Teuton, Jeremy and Kocakaya, Ebru and Summak, G{\"o}k{\c c}e Ya{\u g}mur and Hanspers, Kristina and Kutmon, Martina and Coort, Susan and Eijssen, Lars and Ehrhart, Friederike and Rex, Devasahayam Arokia Balaya and Slenter, Denise and Martens, Marvin and Pham, Nhung and Haw, Robin and Jassal, Bijay and Matthews, Lisa and Orlic-Milacic, Marija and Senff Ribeiro, Andrea and Rothfels, Karen and Shamovsky, Veronica and Stephan, Ralf and Sevilla, Cristoffer and Varusai, Thawfeek and Ravel, Jean-Marie and Fraser, Rupsha and Ortseifen, Vera and Marchesi, Silvia and Gawron, Piotr and Smula, Ewa and Heirendt, Laurent and Satagopam, Venkata and Wu, Guanming and Riutta, Anders and Golebiewski, Martin and Owen, Stuart and Goble, Carole and Hu, Xiaoming and Overall, Rupert W and Maier, Dieter and Bauch, Angela and Gyori, Benjamin M and Bachman, John A and Vega, Carlos and Grou{\`e}s, Valentin and Vazquez, Miguel and Porras, Pablo and Licata, Luana and Iannuccelli, Marta and Sacco, Francesca and Nesterova, Anastasia and Yuryev, Anton and de Waard, Anita and Turei, Denes and Luna, Augustin and Babur, Ozgun and Soliman, Sylvain and Valdeolivas, Alberto and Esteban-Medina, Marina and Pe{\~n}a-Chilet, Maria and Rian, Kinza and Helikar, Tom{\'a}{\v s} and Puniya, Bhanwar Lal and Modos, Dezso and Treveil, Agatha and Olbei, Marton and De Meulder, Bertrand and Ballereau, Stephane and Dugourd, Aur{\'e}lien and Naldi, Aur{\'e}lien and No{\"e}l, Vincent and Calzone, Laurence and Sander, Chris and Demir, Emek and Korcsmaros, Tamas and Freeman, Tom C and Aug{\'e}, Franck and Beckmann, Jacques S and Hasenauer, Jan and Wolkenhauer, Olaf and Wilighagen, Egon L and Pico, Alexander R and Evelo, Chris T and Gillespie, Marc E and Stein, Lincoln D and Hermjakob, Henning and D{\textquoteright}Eustachio, Peter and Saez-Rodriguez, Julio and Dopazo, Joaquin and Valencia, Alfonso and Kitano, Hiroaki and Barillot, Emmanuel and Auffray, Charles and Balling, Rudi and Schneider, Reinhard} } @article {701, title = {CSVS, a crowdsourcing database of the Spanish population genetic variability.}, journal = {Nucleic Acids Res}, volume = {49}, year = {2021}, month = {2021 01 08}, pages = {D1130-D1137}, abstract = {

The knowledge of the genetic variability of the local population is of utmost importance in personalized medicine and has been revealed as a critical factor for the discovery of new disease variants. Here, we present the Collaborative Spanish Variability Server (CSVS), which currently contains more than 2000 genomes and exomes of unrelated Spanish individuals. This database has been generated in a collaborative crowdsourcing effort collecting sequencing data produced by local genomic projects and for other purposes. Sequences have been grouped by ICD10 upper categories. A web interface allows querying the database removing one or more ICD10 categories. In this way, aggregated counts of allele frequencies of the pseudo-control Spanish population can be obtained for diseases belonging to the category removed. Interestingly, in addition to pseudo-control studies, some population studies can be made, as, for example, prevalence of pharmacogenomic variants, etc. In addition, this genomic data has been used to define the first Spanish Genome Reference Panel (SGRP1.0) for imputation. This is the first local repository of variability entirely produced by a crowdsourcing effort and constitutes an example for future initiatives to characterize local variability worldwide. CSVS is also part of the GA4GH Beacon network. CSVS can be accessed at: http://csvs.babelomics.org/.

}, keywords = {Alleles, Chromosome Mapping, Crowdsourcing, Databases, Genetic, Exome, Gene Frequency, Genetic Variation, Genetics, Population, Genome, Human, Genomics, Humans, Internet, Precision Medicine, Software, Spain}, issn = {1362-4962}, doi = {10.1093/nar/gkaa794}, author = {Pe{\~n}a-Chilet, Maria and Rold{\'a}n, Gema and Perez-Florido, Javier and Ortuno, Francisco M and Carmona, Rosario and Aquino, Virginia and L{\'o}pez-L{\'o}pez, Daniel and Loucera, Carlos and Fernandez-Rueda, Jose L and Gallego, Asunci{\'o}n and Garcia-Garcia, Francisco and Gonz{\'a}lez-Neira, Anna and Pita, Guillermo and N{\'u}{\~n}ez-Torres, Roc{\'\i}o and Santoyo-L{\'o}pez, Javier and Ayuso, Carmen and Minguez, Pablo and Avila-Fernandez, Almudena and Corton, Marta and Moreno-Pelayo, Miguel {\'A}ngel and Morin, Mat{\'\i}as and Gallego-Martinez, Alvaro and Lopez-Escamez, Jose A and Borrego, Salud and Anti{\v n}olo, Guillermo and Amigo, Jorge and Salgado-Garrido, Josefa and Pasalodos-Sanchez, Sara and Morte, Beatriz and Carracedo, {\'A}ngel and Alonso, {\'A}ngel and Dopazo, Joaquin} } @article {696, title = {Community Assessment of the Predictability of Cancer Protein and Phosphoprotein Levels from Genomics and Transcriptomics.}, journal = {Cell Syst}, volume = {11}, year = {2020}, month = {2020 08 26}, pages = {186-195.e9}, abstract = {

Cancer is driven by genomic alterations, but the processes causing this disease are largely performed by proteins. However, proteins are harder and more expensive to measure than genes and transcripts. To catalyze developments of methods to infer protein levels from other omics measurements, we leveraged crowdsourcing via the NCI-CPTAC DREAM proteogenomic challenge. We asked for methods to predict protein and phosphorylation levels from genomic and transcriptomic data in cancer patients. The best performance was achieved by an ensemble of models, including as predictors transcript level of the corresponding genes, interaction between genes, conservation across tumor types, and phosphosite proximity for phosphorylation prediction. Proteins from metabolic pathways and complexes were the best and worst predicted, respectively. The performance of even the best-performing model was modest, suggesting that many proteins are strongly regulated through translational control and degradation. Our results set a reference for the limitations of computational inference in proteogenomics. A record of this paper{\textquoteright}s transparent peer review process is included in the Supplemental Information.

}, keywords = {Crowdsourcing, Female, Genomics, Humans, Machine Learning, Male, Neoplasms, Phosphoproteins, Proteins, Proteomics, Transcriptome}, issn = {2405-4720}, doi = {10.1016/j.cels.2020.06.013}, author = {Yang, Mi and Petralia, Francesca and Li, Zhi and Li, Hongyang and Ma, Weiping and Song, Xiaoyu and Kim, Sunkyu and Lee, Heewon and Yu, Han and Lee, Bora and Bae, Seohui and Heo, Eunji and Kaczmarczyk, Jan and St{\k e}pniak, Piotr and Warcho{\l}, Micha{\l} and Yu, Thomas and Calinawan, Anna P and Boutros, Paul C and Payne, Samuel H and Reva, Boris and Boja, Emily and Rodriguez, Henry and Stolovitzky, Gustavo and Guan, Yuanfang and Kang, Jaewoo and Wang, Pei and Feny{\"o}, David and Saez-Rodriguez, Julio} } @article {689, title = {COVID-19 Disease Map, building a computational repository of SARS-CoV-2 virus-host interaction mechanisms.}, journal = {Sci Data}, volume = {7}, year = {2020}, month = {2020 05 05}, pages = {136}, keywords = {Betacoronavirus, Computational Biology, Coronavirus Infections, COVID-19, Databases, Factual, Host Microbial Interactions, Host-Pathogen Interactions, Humans, International Cooperation, Models, Biological, Pandemics, Pneumonia, Viral, SARS-CoV-2}, issn = {2052-4463}, doi = {10.1038/s41597-020-0477-8}, author = {Ostaszewski, Marek and Mazein, Alexander and Gillespie, Marc E and Kuperstein, Inna and Niarakis, Anna and Hermjakob, Henning and Pico, Alexander R and Willighagen, Egon L and Evelo, Chris T and Hasenauer, Jan and Schreiber, Falk and Dr{\"a}ger, Andreas and Demir, Emek and Wolkenhauer, Olaf and Furlong, Laura I and Barillot, Emmanuel and Dopazo, Joaquin and Orta-Resendiz, Aurelio and Messina, Francesco and Valencia, Alfonso and Funahashi, Akira and Kitano, Hiroaki and Auffray, Charles and Balling, Rudi and Schneider, Reinhard} } @article {612, title = {Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen.}, journal = {Nat Commun}, volume = {10}, year = {2019}, month = {2019 06 17}, pages = {2674}, abstract = {

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca{\textquoteright}s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60\% of combinations. However, 20\% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.

}, keywords = {ADAM17 Protein, Antineoplastic Combined Chemotherapy Protocols, Benchmarking, Biomarkers, Tumor, Cell Line, Tumor, Computational Biology, Datasets as Topic, Drug Antagonism, Drug Resistance, Neoplasm, Drug Synergism, Genomics, Humans, Molecular Targeted Therapy, mutation, Neoplasms, pharmacogenetics, Phosphatidylinositol 3-Kinases, Phosphoinositide-3 Kinase Inhibitors, Treatment Outcome}, issn = {2041-1723}, doi = {10.1038/s41467-019-09799-2}, author = {Menden, Michael P and Wang, Dennis and Mason, Mike J and Szalai, Bence and Bulusu, Krishna C and Guan, Yuanfang and Yu, Thomas and Kang, Jaewoo and Jeon, Minji and Wolfinger, Russ and Nguyen, Tin and Zaslavskiy, Mikhail and Jang, In Sock and Ghazoui, Zara and Ahsen, Mehmet Eren and Vogel, Robert and Neto, Elias Chaibub and Norman, Thea and Tang, Eric K Y and Garnett, Mathew J and Veroli, Giovanni Y Di and Fawell, Stephen and Stolovitzky, Gustavo and Guinney, Justin and Dry, Jonathan R and Saez-Rodriguez, Julio} } @article {403, title = {A comparison of mechanistic signaling pathway activity analysis methods.}, journal = {Brief Bioinform}, volume = {20}, year = {2019}, month = {2019 09 27}, pages = {1655-1668}, abstract = {

Understanding the aspects of cell functionality that account for disease mechanisms or drug modes of action is a main challenge for precision medicine. Classical gene-based approaches ignore the modular nature of most human traits, whereas conventional pathway enrichment approaches produce only illustrative results of limited practical utility. Recently, a family of new methods has emerged that change the focus from the whole pathways to the definition of elementary subpathways within them that have any mechanistic significance and to the study of their activities. Thus, mechanistic pathway activity (MPA) methods constitute a new paradigm that allows recoding poorly informative genomic measurements into cell activity quantitative values and relate them to phenotypes. Here we provide a review on the MPA methods available and explain their contribution to systems medicine approaches for addressing challenges in the diagnostic and treatment of complex diseases.

}, keywords = {Algorithms, Humans, Postmortem Changes, Signal Transduction, Systems biology, Transcriptome}, issn = {1477-4054}, doi = {10.1093/bib/bby040}, author = {Amadoz, Alicia and Hidalgo, Marta R and Cubuk, Cankut and Carbonell-Caballero, Jos{\'e} and Dopazo, Joaquin} } @article {428, title = {A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection}, journal = {Nature Communications}, volume = {9}, year = {2018}, month = {Jan-12-2018}, doi = {10.1038/s41467-018-06735-8}, url = {http://www.nature.com/articles/s41467-018-06735-8http://www.nature.com/articles/s41467-018-06735-8.pdfhttp://www.nature.com/articles/s41467-018-06735-8.pdfhttp://www.nature.com/articles/s41467-018-06735-8}, author = {Fourati, Slim and Talla, Aarthi and Mahmoudian, Mehrad and Burkhart, Joshua G. and Kl{\'e}n, Riku and Henao, Ricardo and Yu, Thomas and Ayd{\i}n, Zafer and Yeung, Ka Yee and Ahsen, Mehmet Eren and Almugbel, Reem and Jahandideh, Samad and Liang, Xiao and Nordling, Torbj{\"o}rn E. M. and Shiga, Motoki and Stanescu, Ana and Vogel, Robert and Pandey, Gaurav and Chiu, Christopher and McClain, Micah T. and Woods, Christopher W. and Ginsburg, Geoffrey S. and Elo, Laura L. and Tsalik, Ephraim L. and Mangravite, Lara M. and Sieberts, Solveig K.} } @article {1198, title = {Chronic subordination stress selectively downregulates the insulin signaling pathway in liver and skeletal muscle but not in adipose tissue of male mice.}, journal = {Stress (Amsterdam, Netherlands)}, year = {2016}, month = {2016 Mar 7}, pages = {1-11}, abstract = {Chronic stress has been associated with obesity, glucose intolerance, and insulin resistance. We developed a model of chronic psychosocial stress (CPS) in which subordinate mice are vulnerable to obesity and the metabolic-like syndrome while dominant mice exhibit a healthy metabolic phenotype. Here we tested the hypothesis that the metabolic difference between subordinate and dominant mice is associated with changes in functional pathways relevant for insulin sensitivity, glucose and lipid homeostasis. Male mice were exposed to CPS for four weeks and fed either a standard diet or a high-fat diet (HFD). We first measured, by real-time PCR candidate genes, in the liver, skeletal muscle, and the perigonadal white adipose tissue (pWAT). Subsequently, we used a probabilistic analysis approach to analyze different ways in which signals can be transmitted across the pathways in each tissue. Results showed that subordinate mice displayed a drastic downregulation of the insulin pathway in liver and muscle, indicative of insulin resistance, already on standard diet. Conversely, pWAT showed molecular changes suggestive of facilitated fat deposition in an otherwise insulin-sensitive tissue. The molecular changes in subordinate mice fed a standard diet were greater compared to HFD-fed controls. Finally, dominant mice maintained a substantially normal metabolic and molecular phenotype even when fed a HFD. Overall, our data demonstrate that subordination stress is a potent stimulus for the downregulation of the insulin signaling pathway in liver and muscle and a major risk factor for the development of obesity, insulin resistance, and type 2 diabetes mellitus.}, keywords = {Adipose tissue, insulin, IRS1, IRS2, metabolic syndrome, obesity, pathway analysis}, issn = {1607-8888}, doi = {10.3109/10253890.2016.1151491}, url = {http://www.tandfonline.com/doi/abs/10.3109/10253890.2016.1151491?journalCode=ists20}, author = {Sanghez, Valentina and Cubuk, Cankut and Sebasti{\'a}n-Leon, Patricia and Carobbio, Stefania and Dopazo, Joaquin and Vidal-Puig, Antonio and Bartolomucci, Alessandro} } @article {1132, title = {Combining tumor genome simulation with crowdsourcing to benchmark somatic single-nucleotide-variant detection.}, journal = {Nature methods}, year = {2015}, month = {2015 May 18}, abstract = {The detection of somatic mutations from cancer genome sequences is key to understanding the genetic basis of disease progression, patient survival and response to therapy. Benchmarking is needed for tool assessment and improvement but is complicated by a lack of gold standards, by extensive resource requirements and by difficulties in sharing personal genomic information. To resolve these issues, we launched the ICGC-TCGA DREAM Somatic Mutation Calling Challenge, a crowdsourced benchmark of somatic mutation detection algorithms. Here we report the BAMSurgeon tool for simulating cancer genomes and the results of 248 analyses of three in silico tumors created with it. Different algorithms exhibit characteristic error profiles, and, intriguingly, false positives show a trinucleotide profile very similar to one found in human tumors. Although the three simulated tumors differ in sequence contamination (deviation from normal cell sequence) and in subclonality, an ensemble of pipelines outperforms the best individual pipeline in all cases. BAMSurgeon is available at https://github.com/adamewing/bamsurgeon/.}, keywords = {cancer, NGS, variant calling}, issn = {1548-7105}, doi = {10.1038/nmeth.3407}, url = {http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.3407.html}, author = {Ewing, Adam D and Houlahan, Kathleen E and Hu, Yin and Ellrott, Kyle and Caloian, Cristian and Yamaguchi, Takafumi N and Bare, J Christopher and P{\textquoteright}ng, Christine and Waggott, Daryl and Sabelnykova, Veronica Y and Kellen, Michael R and Norman, Thea C and Haussler, David and Friend, Stephen H and Stolovitzky, Gustavo and Margolin, Adam A and Stuart, Joshua M and Boutros, Paul C}, editor = {ICGC-TCGA DREAM Somatic Mutation Calling Challenge participants and Liu Xi and Ninad Dewal and Yu Fan and Wenyi Wang and David Wheeler and Andreas Wilm and Grace Hui Ting and Chenhao Li and Denis Bertrand and Niranjan Nagarajan and Qing-Rong Chen and Chih-Hao Hsu and Ying Hu and Chunhua Yan and Warren Kibbe and Daoud Meerzaman and Kristian Cibulskis and Mara Rosenberg and Louis Bergelson and Adam Kiezun and Amie Radenbaugh and Anne-Sophie Sertier and Anthony Ferrari and Laurie Tonton and Kunal Bhutani and Nancy F Hansen and Difei Wang and Lei Song and Zhongwu Lai and Liao, Yang and Shi, Wei and Carbonell-Caballero, Jos{\'e} and Joaqu{\'\i}n Dopazo and Cheryl C K Lau and Justin Guinney} } @article {1160, title = {Comparative gene expression study of the vestibular organ of the Igf1 deficient mouse using whole-transcript arrays.}, journal = {Hearing research}, year = {2015}, month = {2015 Sep 1}, abstract = {The auditory and vestibular organs form the inner ear and have a common developmental origin. Insulin like growth factor 1 (IGF-1) has a central role in the development of the cochlea and maintenance of hearing. Its deficiency causes sensorineural hearing loss in man and mice. During chicken early development, IGF-1 modulates neurogenesis of the cochleovestibular ganglion but no further studies have been conducted to explore the potential role of IGF-1 in the vestibular system. In this study we have compared the whole transcriptome of the vestibular organ from wild type and Igf1(-/-) mice at different developmental and postnatal times. RNA was prepared from E18.5, P15 and P90 vestibular organs of Igf1(-/-) and Igf1(+/+) mice and the transcriptome analysed in triplicates using Affymetrix{\textregistered} Mouse Gene 1.1 ST Array Plates. These plates are whole-transcript arrays that include probes to measure both messenger (mRNA) and long intergenic non-coding RNA transcripts (lincRNA), with a coverage of over 28 thousand coding transcripts and over 7 thousands non-coding transcripts. Given the complexity of the data we used two different methods VSN-RMA and mmBGX to analyse and compare the data. This is to better evaluate the number of false positives and to quantify uncertainty of low signals. We identified a number of differentially expressed genes that we described using functional analysis and validated using RT-qPCR. The morphology of the vestibular organ did not show differences between genotypes and no evident alterations were observed in the vestibular sensory areas of the null mice. However, well-defined cellular alterations were found in the vestibular neurons with respect their number and size. Although these mice did not show a dramatic vestibular phenotype, we conducted a functional analysis on differentially expressed genes between genotypes and across time. This was with the aim to identify new pathways that are involved in the development of the vestibular organ as well as pathways that maybe affected by the lack of IGF-1 and be associated to the morphological changes of the vestibular neurons that we observed in the Igf1(-/-) mice.}, issn = {1878-5891}, doi = {10.1016/j.heares.2015.08.016}, url = {http://www.sciencedirect.com/science/article/pii/S0378595515001835}, author = {Rodr{\'\i}guez-de la Rosa, Lourdes and S{\'a}nchez-Calder{\'o}n, Hortensia and Contreras, Julio and Murillo-Cuesta, Silvia and Falagan, Sandra and Avenda{\~n}o, Carlos and Joaqu{\'\i}n Dopazo and Varela-Nieto, Isabel and Milo, Marta} } @article {1162, title = {Concurrent and Accurate Short Read Mapping on Multicore Processors.}, journal = {IEEE/ACM transactions on computational biology and bioinformatics / IEEE, ACM}, volume = {12}, year = {2015}, month = {2015 Sep-Oct}, pages = {995-1007}, abstract = {We introduce a parallel aligner with a work-flow organization for fast and accurate mapping of RNA sequences on servers equipped with multicore processors. Our software, [Formula: see text] ([Formula: see text] is an open-source application. The software is available at http://www.opencb.org, exploits a suffix array to rapidly map a large fraction of the RNA fragments (reads), as well as leverages the accuracy of the Smith-Waterman algorithm to deal with conflictive reads. The aligner is enhanced with a careful strategy to detect splice junctions based on an adaptive division of RNA reads into small segments (or seeds), which are then mapped onto a number of candidate alignment locations, providing crucial information for the successful alignment of the complete reads. The experimental results on a platform with Intel multicore technology report the parallel performance of [Formula: see text], on RNA reads of 100-400 nucleotides, which excels in execution time/sensitivity to state-of-the-art aligners such as TopHat 2+Bowtie 2, MapSplice, and STAR.}, keywords = {HPC, NGS, short real mapping}, issn = {1557-9964}, doi = {10.1109/TCBB.2015.2392077}, url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=\&arnumber=7010005}, author = {Martinez, Hector and T{\'a}rraga, Joaqu{\'\i}n and Medina, Ignacio and Barrachina, Sergio and Castillo, Maribel and Dopazo, Joaquin and Quintana-Orti, Enrique S} } @article {1042, title = {Combined genetic and high-throughput strategies for molecular diagnosis of inherited retinal dystrophies.}, journal = {PloS one}, volume = {9}, year = {2014}, month = {2014}, pages = {e88410}, abstract = {Most diagnostic laboratories are confronted with the increasing demand for molecular diagnosis from patients and families and the ever-increasing genetic heterogeneity of visual disorders. Concerning Retinal Dystrophies (RD), almost 200 causative genes have been reported to date, and most families carry private mutations. We aimed to approach RD genetic diagnosis using all the available genetic information to prioritize candidates for mutational screening, and then restrict the number of cases to be analyzed by massive sequencing. We constructed and optimized a comprehensive cosegregation RD-chip based on SNP genotyping and haplotype analysis. The RD-chip allows to genotype 768 selected SNPs (closely linked to 100 RD causative genes) in a single cost-, time-effective step. Full diagnosis was attained in 17/36 Spanish pedigrees, yielding 12 new and 12 previously reported mutations in 9 RD genes. The most frequently mutated genes were USH2A and CRB1. Notably, RD3-up to now only associated to Leber Congenital Amaurosis- was identified as causative of Retinitis Pigmentosa. The main assets of the RD-chip are: i) the robustness of the genetic information that underscores the most probable candidates, ii) the invaluable clues in cases of shared haplotypes, which are indicative of a common founder effect, and iii) the detection of extended haplotypes over closely mapping genes, which substantiates cosegregation, although the assumptions in which the genetic analysis is based could exceptionally lead astray. The combination of the genetic approach with whole exome sequencing (WES) greatly increases the diagnosis efficiency, and revealed novel mutations in USH2A and GUCY2D. Overall, the RD-chip diagnosis efficiency ranges from 16\% in dominant, to 80\% in consanguineous recessive pedigrees, with an average of 47\%, well within the upper range of massive sequencing approaches, highlighting the validity of this time- and cost-effective approach whilst high-throughput methodologies become amenable for routine diagnosis in medium sized labs.}, issn = {1932-6203}, doi = {10.1371/journal.pone.0088410}, url = {http://dx.plos.org/10.1371/journal.pone.0088410}, author = {de Castro-Mir{\'o}, Marta and Pomares, Esther and Lor{\'e}s-Motta, Laura and Tonda, Raul and Joaqu{\'\i}n Dopazo and Marfany, Gemma and Gonz{\`a}lez-Duarte, Roser} } @article {1077, title = {A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium.}, journal = {Nature biotechnology}, volume = {32}, year = {2014}, month = {2014 Aug 24}, pages = {903{\textendash}914}, abstract = {We present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the US Food and Drug Administration. Examining Illumina HiSeq, Life Technologies SOLiD and Roche 454 platforms at multiple laboratory sites using reference RNA samples with built-in controls, we assess RNA sequencing (RNA-seq) performance for junction discovery and differential expression profiling and compare it to microarray and quantitative PCR (qPCR) data using complementary metrics. At all sequencing depths, we discover unannotated exon-exon junctions, with >80\% validated by qPCR. We find that measurements of relative expression are accurate and reproducible across sites and platforms if specific filters are used. In contrast, RNA-seq and microarrays do not provide accurate absolute measurements, and gene-specific biases are observed for all examined platforms, including qPCR. Measurement performance depends on the platform and data analysis pipeline, and variation is large for transcript-level profiling. The complete SEQC data sets, comprising >100 billion reads (10Tb), provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings.}, keywords = {NGS, RNA-seq, SEQC}, issn = {1546-1696}, doi = {10.1038/nbt.2957}, url = {http://www.nature.com/nbt/journal/vaop/ncurrent/full/nbt.2957.html}, author = {Su, Z. and Labaj, P.P. and .... and Dopazo, J. and .... and Mason, C.E. and Shi, L} } @article {1074, title = {A Comprehensive DNA Methylation Profile of Epithelial-to-Mesenchymal Transition.}, journal = {Cancer research}, volume = {74}, number = {19}, year = {2014}, month = {2014 Aug 8}, pages = {5608{\textendash}19}, abstract = {Epithelial-to-mesenchymal transition (EMT) is a plastic process in which fully differentiated epithelial cells are converted into poorly differentiated, migratory and invasive mesenchymal cells and it has been related to the metastasis potential of tumors. This is a reversible process and cells can also eventually undergo mesenchymal-to-epithelial transition (MET). The existence of a dynamic EMT process suggests the involvement of epigenetic shifts in the phenotype. Herein, we obtained the DNA methylomes at single-base resolution of MDCK cells undergoing epithelial-to-mesenchymal transition (EMT) and translated the identified differentially methylated regions (DMRs) to human breast cancer cells undergoing a gain of migratory and invasive capabilities associated with the EMT phenotype. We noticed dynamic and reversible changes of DNA methylation, both on promoter sequences and gene-bodies in association with transcription regulation of EMT-related genes. Most importantly, the identified DNA methylation markers of EMT were present in primary mammary tumors in association with the epithelial or the mesenchymal phenotype of the studied breast cancer samples.}, keywords = {Methyl-Seq, Methylomics, Next Generation Sequencing}, issn = {1538-7445}, doi = {10.1158/0008-5472.CAN-13-3659}, url = {http://www.ncbi.nlm.nih.gov/pubmed/25106427}, author = {Carmona, F Javier and Davalos, Veronica and Vidal, Enrique and Gomez, Antonio and Heyn, Holger and Hashimoto, Yutaka and Vizoso, Miguel and Martinez-Cardus, Anna and Sayols, Sergi and Ferreira, Humberto and Sanchez-Mut, Jose and Moran, Sebastian and Margeli, Mireia and Castella, Eva and Berdasco, Maria and Stefansson, Olafur Andri and Eyfjord, Jorunn E and Gonzalez-Suarez, Eva and Dopazo, Joaquin and Orozco, Modesto and Gut, Ivo and Esteller, Manel} } @article {1047, title = {Capturing the biological impact of CDKN2A and MC1R genes as an early predisposing event in melanoma and non melanoma skin cancer.}, journal = {Oncotarget}, year = {2013}, month = {2013 Dec 16}, abstract = {Germline mutations in CDKN2A and/or red hair color variants in MC1R genes are associated with an increased susceptibility to develop cutaneous melanoma or non melanoma skin cancer. We studied the impact of the CDKN2A germinal mutation p.G101W and MC1R variants on gene expression and transcription profiles associated with skin cancer. To this end we set-up primary skin cell co-cultures from siblings of melanoma prone-families that were later analyzed using the expression array approach. As a result, we found that 1535 transcripts were deregulated in CDKN2A mutated cells, with over-expression of immunity-related genes (HLA-DPB1, CLEC2B, IFI44, IFI44L, IFI27, IFIT1, IFIT2, SP110 and IFNK) and down-regulation of genes playing a role in the Notch signaling pathway. 3570 transcripts were deregulated in MC1R variant carriers. In particular, genes related to oxidative stress and DNA damage pathways were up-regulated as well as genes associated with neurodegenerative diseases such as Parkinson{\textquoteright}s, Alzheimer and Huntington. Finally, we observed that the expression signatures indentified in phenotypically normal cells carrying CDKN2A mutations or MC1R variants are maintained in skin cancer tumors (melanoma and squamous cell carcinoma). These results indicate that transcriptome deregulation represents an early event critical for skin cancer development.}, issn = {1949-2553}, url = {http://www.impactjournals.com/oncotarget/index.php?journal=oncotarget\&page=article\&op=view\&path\%5B\%5D=1444\&path\%5B\%5D=1824}, author = {Puig-Butille, Joan Anton and Escamez, Maria Jos{\'e} and Garcia-Garcia, Francisco and Tell-Marti, Gemma and Fabra, Angels and Mart{\'\i}nez-Santamar{\'\i}a, Luc{\'\i}a and Badenas, Celia and Aguilera, Paula and Pevida, Marta and Joaqu{\'\i}n Dopazo and Del Rio, Marcela and Puig, Susana} } @article {916, title = {CellBase, a comprehensive collection of RESTful web services for retrieving relevant biological information from heterogeneous sources.}, journal = {Nucleic acids research}, volume = {40}, year = {2012}, month = {2012 Jul}, pages = {W609-14}, abstract = {During the past years, the advances in high-throughput technologies have produced an unprecedented growth in the number and size of repositories and databases storing relevant biological data. Today, there is more biological information than ever but, unfortunately, the current status of many of these repositories is far from being optimal. Some of the most common problems are that the information is spread out in many small databases; frequently there are different standards among repositories and some databases are no longer supported or they contain too specific and unconnected information. In addition, data size is increasingly becoming an obstacle when accessing or storing biological data. All these issues make very difficult to extract and integrate information from different sources, to analyze experiments or to access and query this information in a programmatic way. CellBase provides a solution to the growing necessity of integration by easing the access to biological data. CellBase implements a set of RESTful web services that query a centralized database containing the most relevant biological data sources. The database is hosted in our servers and is regularly updated. CellBase documentation can be found at http://docs.bioinfo.cipf.es/projects/cellbase.}, issn = {1362-4962}, doi = {10.1093/nar/gks575}, url = {http://nar.oxfordjournals.org/content/40/W1/W609.long}, author = {Bleda, Marta and T{\'a}rraga, Joaqu{\'\i}n and De Maria, Alejandro and Salavert, Francisco and Garc{\'\i}a-Alonso, Luz and Celma, Matilde and Martin, Ainoha and Dopazo, Joaquin and Medina, Ignacio} } @article {20028698, title = {Changes in the pattern of DNA methylation associate with twin discordance in systemic lupus erythematosus.}, journal = {Genome research}, volume = {20}, year = {2010}, month = {2010 Feb}, pages = {170-9}, abstract = {

Monozygotic (MZ) twins are partially concordant for most complex diseases, including autoimmune disorders. Whereas phenotypic concordance can be used to study heritability, discordance suggests the role of non-genetic factors. In autoimmune diseases, environmentally driven epigenetic changes are thought to contribute to their etiology. Here we report the first high-throughput and candidate sequence analyses of DNA methylation to investigate discordance for autoimmune disease in twins. We used a cohort of MZ twins discordant for three diseases whose clinical signs often overlap: systemic lupus erythematosus (SLE), rheumatoid arthritis, and dermatomyositis. Only MZ twins discordant for SLE featured widespread changes in the DNA methylation status of a significant number of genes. Gene ontology analysis revealed enrichment in categories associated with immune function. Individual analysis confirmed the existence of DNA methylation and expression changes in genes relevant to SLE pathogenesis. These changes occurred in parallel with a global decrease in the 5-methylcytosine content that was concomitantly accompanied with changes in DNA methylation and expression levels of ribosomal RNA genes, although no changes in repetitive sequences were found. Our findings not only identify potentially relevant DNA methylation markers for the clinical characterization of SLE patients but also support the notion that epigenetic changes may be critical in the clinical manifestations of autoimmune disease.

}, author = {Javierre, Biola M and Fernandez, Agustin F and Richter, Julia and Fatima Al-Shahrour and Martin-Subero, J Ignacio and Rodriguez-Ubreva, Javier and Berdasco, Maria and Fraga, Mario F and O{\textquoteright}Hanlon, Terrance P and Rider, Lisa G and Jacinto, Filipe V and Lopez-Longo, F Javier and Dopazo, Joaquin and Forn, Marta and Peinado, Miguel A and Carre{\~n}o, Luis and Sawalha, Amr H and Harley, John B and Siebert, Reiner and Esteller, Manel and Miller, Frederick W and Ballestar, Esteban} } @article {17597009, title = {CLEAR-test: combining inference for differential expression and variability in microarray data analysis}, journal = {J Biomed Inform}, volume = {41}, number = {1}, year = {2008}, note = {

Valls, Joan Grau, Monica Sole, Xavier Hernandez, Pilar Montaner, David Dopazo, Joaquin Peinado, Miguel A Capella, Gabriel Moreno, Victor Pujana, Miguel Angel Comparative Study Research Support, Non-U.S. Gov{\textquoteright}t United States Journal of biomedical informatics J Biomed Inform. 2008 Feb;41(1):33-45. Epub 2007 May 17.

}, pages = {33-45}, abstract = {

A common goal of microarray experiments is to detect genes that are differentially expressed under distinct experimental conditions. Several statistical tests have been proposed to determine whether the observed changes in gene expression are significant. The t-test assigns a score to each gene on the basis of changes in its expression relative to its estimated variability, in such a way that genes with a higher score (in absolute values) are more likely to be significant. Most variants of the t-test use the complete set of genes to influence the variance estimate for each single gene. However, no inference is made in terms of the variability itself. Here, we highlight the problem of low observed variances in the t-test, when genes with relatively small changes are declared differentially expressed. Alternatively, the z-test could be used although, unlike the t-test, it can declare differentially expressed genes with high observed variances. To overcome this, we propose to combine the z-test, which focuses on large changes, with a chi(2) test to evaluate variability. We call this procedure CLEAR-test and we provide a combined p-value that offers a compromise between both aspects. Analysis of three publicly available microarray datasets reveals the greater performance of the CLEAR-test relative to the t-test and alternative methods. Finally, empirical and simulated data analyses demonstrate the greater reproducibility and statistical power of the CLEAR-test and z-test with respect to current alternative methods. In addition, the CLEAR-test improves the z-test by capturing reproducible genes with high variability.

}, keywords = {*Algorithms Artificial Intelligence *Data Interpretation, Statistical Gene Expression Profiling/*methods Gene Expression Regulation/*physiology Oligonucleotide Array Sequence Analysis/*methods Proteome/*metabolism Signal Transduction/*physiology}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=17597009}, author = {Valls, J. and Grau, M. and Sole, X. and Hernandez, P. and Montaner, D. and Dopazo, J. and Peinado, M. A. and Capella, G. and Moreno, V. and Pujana, M. A.} } @inbook {473, title = {Comparative genomics-based prediction of protein function}, booktitle = {Methods in Molecular Biology}, volume = {439}, year = {2008}, publisher = {M. Starkey and R. Elaswarapu, Humana press}, organization = {M. Starkey and R. Elaswarapu, Humana press}, url = {http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-188-8_26}, author = {Gabald{\'o}n, T.} } @article {18697870, title = {Controlled ovarian stimulation induces a functional genomic delay of the endometrium with potential clinical implications}, journal = {J Clin Endocrinol Metab}, volume = {93}, number = {11}, year = {2008}, note = {

Horcajadas, Jose A Minguez, Pablo Dopazo, Joaquin Esteban, Francisco J Dominguez, Francisco Giudice, Linda C Pellicer, Antonio Simon, Carlos Research Support, Non-U.S. Gov{\textquoteright}t United States The Journal of clinical endocrinology and metabolism J Clin Endocrinol Metab. 2008 Nov;93(11):4500-10. Epub 2008 Aug 12.

}, pages = {4500-10}, abstract = {

CONTEXT: Controlled ovarian stimulation induces morphological, biochemical, and functional genomic modifications of the human endometrium during the window of implantation. OBJECTIVE: Our objective was to compare the gene expression profile of the human endometrium in natural vs. controlled ovarian stimulation cycles throughout the early-mid secretory transition using microarray technology. METHOD: Microarray data from 49 endometrial biopsies obtained from LH+1 to LH+9 (n=25) in natural cycles and from human chorionic gonadotropin (hCG) +1 to hCG+9 in controlled ovarian stimulation cycles (n=24) were analyzed using different methods, such as clustering, profiling of biological processes, and selection of differentially expressed genes, as implemented in Gene Expression Pattern Analysis Suite and Babelomics programs. RESULTS: Endometria from natural cycles followed different genomic patterns compared with controlled ovarian stimulation cycles in the transition from the pre-receptive (days LH/hCG+1 until LH/hCG+5) to the receptive phase (day LH+7/hCG+7). Specifically, we have demonstrated the existence of a 2-d delay in the activation/repression of two clusters composed by 218 and 133 genes, respectively, on day hCG+7 vs. LH+7. Many of these delayed genes belong to the class window of implantation genes affecting basic biological processes in the receptive endometrium. CONCLUSIONS: These results demonstrate that gene expression profiling of the endometrium is different between natural and controlled ovarian stimulation cycles in the receptive phase. Identification of these differentially regulated genes can be used to understand the different developmental profiles of receptive endometrium during controlled ovarian stimulation and to search for the best controlled ovarian stimulation treatment in terms of minimal endometrial impact.

}, keywords = {Algorithms Chorionic Gonadotropin/genetics Endometrium/cytology/pathology/*physiology/physiopathology Female Gene Expression Regulation Genome, Human Glutathione Peroxidase/genetics Humans Insulin-Like Growth Factor Binding Proteins/genetics Luteal Phase/physiology Luteinizing Hormone/genetics Menstrual Cycle Oligonucleotide Array Sequence Analysis Ovulation Induction/*methods RNA/genetics/isola}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=18697870}, author = {Horcajadas, J. A. and Minguez, P. and Dopazo, J. and Esteban, F. J. and Dominguez, F. and Giudice, L. C. and Pellicer, A. and Simon, C.} } @inbook {472, title = {The core of a minimal gene set: insights from natural reduced genomes}, booktitle = {Protocells: Bridging nonliving and living matter}, year = {2008}, pages = {347-366}, publisher = {The MIT Press}, organization = {The MIT Press}, address = {USA}, author = {Gabald{\'o}n, T. and Gil, R. and Peret{\'o}, J. and Latorre, A. and Moya, A.} } @article {17941705, title = {Characterization of protein hubs by inferring interacting motifs from protein interactions}, journal = {PLoS Comput Biol}, volume = {3}, number = {9}, year = {2007}, note = {Aragues, Ramon Sali, Andrej Bonet, Jaume Marti-Renom, Marc A Oliva, Baldo PN2 EY016525,/EY/NEI NIH HHS/United States U54 RR022220/RR/NCRR NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov{\textquoteright}t United States PLoS computational biology PLoS Comput Biol. 2007 Sep;3(9):1761-71. Epub 2007 Jul 30.}, pages = {1761-71}, abstract = {The characterization of protein interactions is essential for understanding biological systems. While genome-scale methods are available for identifying interacting proteins, they do not pinpoint the interacting motifs (e.g., a domain, sequence segments, a binding site, or a set of residues). Here, we develop and apply a method for delineating the interacting motifs of hub proteins (i.e., highly connected proteins). The method relies on the observation that proteins with common interaction partners tend to interact with these partners through a common interacting motif. The sole input for the method are binary protein interactions; neither sequence nor structure information is needed. The approach is evaluated by comparing the inferred interacting motifs with domain families defined for 368 proteins in the Structural Classification of Proteins (SCOP). The positive predictive value of the method for detecting proteins with common SCOP families is 75\% at sensitivity of 10\%. Most of the inferred interacting motifs were significantly associated with sequence patterns, which could be responsible for the common interactions. We find that yeast hubs with multiple interacting motifs are more likely to be essential than hubs with one or two interacting motifs, thus rationalizing the previously observed correlation between essentiality and the number of interacting partners of a protein. We also find that yeast hubs with multiple interacting motifs evolve slower than the average protein, contrary to the hubs with one or two interacting motifs. The proposed method will help us discover unknown interacting motifs and provide biological insights about protein hubs and their roles in interaction networks.}, keywords = {Amino Acid Motifs Amino Acid Sequence Binding Sites Computer Simulation *Models, Chemical *Models, Molecular Molecular Sequence Data Protein Binding Protein Interaction Mapping/*methods Proteins/*chemistry Sequence Analysis, Protein/*methods}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=17941705}, author = {Aragues, R. and Sali, A. and Bonet, J. and M. A. Marti-Renom and Oliva, B.} } @inbook {477, title = {Clustering - Class discovery in the post-genomic era}, booktitle = {Fundamentals of data mining in genomics and proteomics}, year = {2007}, publisher = {Springer-Verlag, W. Dubitzky, M. Granzow and D.P. Berrar}, organization = {Springer-Verlag, W. Dubitzky, M. Granzow and D.P. Berrar}, address = {New York, USA}, author = {Dopazo, J.} } @article {18428767, title = {Comparative protein structure modeling using Modeller}, journal = {Curr Protoc Bioinformatics}, volume = {Chapter 5}, year = {2006}, note = {Eswar, Narayanan Webb, Ben Marti-Renom, Marc A Madhusudhan, M S Eramian, David Shen, Min-Yi Pieper, Ursula Sali, Andrej P01 A135707/PHS HHS/United States P01 GM71790/GM/NIGMS NIH HHS/United States R01 GM54762/GM/NIGMS NIH HHS/United States U54 GM62529/GM/NIGMS NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov{\textquoteright}t United States Current protocols in bioinformatics / editoral board, Andreas D. Baxevanis ... [et al.] Curr Protoc Bioinformatics. 2006 Oct;Chapter 5:Unit 5.6.}, pages = {Unit 5 6}, abstract = {Functional characterization of a protein sequence is one of the most frequent problems in biology. This task is usually facilitated by accurate three-dimensional (3-D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described.}, keywords = {Algorithms Amino Acid Sequence Computer Simulation Crystallography/*methods *Models, Chemical *Models, Molecular Molecular Sequence Data Protein Conformation Protein Folding Proteins/*chemistry/*ultrastructure Sequence Analysis, Protein/*methods *Software}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=18428767}, author = {Eswar, N. and Webb, B. and M. A. Marti-Renom and Madhusudhan, M. S. and Eramian, D. and Shen, M. Y. and Pieper, U. and Sali, A.} } @article {16751606, title = {A composite score for predicting errors in protein structure models}, journal = {Protein Sci}, volume = {15}, number = {7}, year = {2006}, note = {Eramian, David Shen, Min-yi Devos, Damien Melo, Francisco Sali, Andrej Marti-Renom, Marc A GM 08284/GM/NIGMS NIH HHS/United States R01 GM54762/GM/NIGMS NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov{\textquoteright}t Research Support, U.S. Gov{\textquoteright}t, Non-P.H.S. United States Protein science : a publication of the Protein Society Protein Sci. 2006 Jul;15(7):1653-66. Epub 2006 Jun 2.}, pages = {1653-66}, abstract = {Reliable prediction of model accuracy is an important unsolved problem in protein structure modeling. To address this problem, we studied 24 individual assessment scores, including physics-based energy functions, statistical potentials, and machine learning-based scoring functions. Individual scores were also used to construct approximately 85,000 composite scoring functions using support vector machine (SVM) regression. The scores were tested for their abilities to identify the most native-like models from a set of 6000 comparative models of 20 representative protein structures. Each of the 20 targets was modeled using a template of <30\% sequence identity, corresponding to challenging comparative modeling cases. The best SVM score outperformed all individual scores by decreasing the average RMSD difference between the model identified as the best of the set and the model with the lowest RMSD (DeltaRMSD) from 0.63 A to 0.45 A, while having a higher Pearson correlation coefficient to RMSD (r=0.87) than any other tested score. The most accurate score is based on a combination of the DOPE non-hydrogen atom statistical potential; surface, contact, and combined statistical potentials from MODPIPE; and two PSIPRED/DSSP scores. It was implemented in the SVMod program, which can now be applied to select the final model in various modeling problems, including fold assignment, target-template alignment, and loop modeling.}, keywords = {*Models, Molecular Models, Theoretical Proteins/*chemistry}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=16751606}, author = {Eramian, D. and Shen, M. Y. and Devos, D. and Melo, F. and Sali, A. and M. A. Marti-Renom} } @article {16870830, title = {Computational approaches for the prediction of protein function in the mitochondrion}, journal = {Am J Physiol Cell Physiol}, volume = {291}, number = {6}, year = {2006}, note = {Gabaldon, Toni Research Support, Non-U.S. Gov{\textquoteright}t Review United States American journal of physiology. Cell physiology Am J Physiol Cell Physiol. 2006 Dec;291(6):C1121-8. Epub 2006 Jul 26.}, pages = {C1121-8}, abstract = {Understanding a complex biological system, such as the mitochondrion, requires the identification of the complete repertoire of proteins targeted to the organelle, the characterization of these, and finally, the elucidation of the functional and physical interactions that occur within the mitochondrion. In the last decade, significant developments have contributed to increase our understanding of the mitochondrion, and among these, computational research has played a significant role. Not only general bioinformatics tools have been applied in the context of the mitochondrion, but also some computational techniques have been specifically developed to address problems that arose from within the mitochondrial research field. In this review the contribution of bioinformatics to mitochondrial biology is addressed through a survey of current computational methods that can be applied to predict which proteins will be localized to the mitochondrion and to unravel their functional interactions.}, keywords = {*Computational Biology *Computer Simulation Humans Mitochondria/*metabolism Mitochondrial Proteins/genetics/*metabolism Mutation}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=16870830}, author = {Gabald{\'o}n, T.} } @article {15670813, title = {Combining data from genomes, Y2H and 3D structure indicates that BolA is a reductase interacting with a glutaredoxin}, journal = {FEBS Lett}, volume = {579}, number = {3}, year = {2005}, note = {Huynen, Martijn A Spronk, Chris A E M Gabaldon, Toni Snel, Berend Research Support, Non-U.S. Gov{\textquoteright}t Netherlands FEBS letters FEBS Lett. 2005 Jan 31;579(3):591-6.}, pages = {591-6}, abstract = {Genomes, functional genomics data and 3D structure reflect different aspects of protein function. Here, we combine these data to predict that BolA, a widely distributed protein family with unknown function, is a reductase that interacts with a glutaredoxin. Comparisons at the 3D structure level as well as at the sequence profile level indicate homology between BolA and OsmC, an enzyme that reduces organic peroxides. Complementary to this, comparative analyses of genomes and genomics data provide strong evidence of an interaction between BolA and the mono-thiol glutaredoxin family. The interaction between BolA and a mono-thiol glutaredoxin is of particular interest because BolA does not, in contrast to its homolog OsmC, have evolutionarily conserved cysteines to provide it with reducing equivalents. We propose that BolA uses the mono-thiol glutaredoxin as the source for these.}, keywords = {*Genome Glutaredoxins Models, Molecular Oxidoreductases/chemistry/*metabolism Phylogeny Protein Conformation}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=15670813}, author = {M. A. Huynen and Spronk, C. A. and Gabald{\'o}n, T. and B. Snel} } @article {16170324, title = {The C-type lectin fold as an evolutionary solution for massive sequence variation}, journal = {Nat Struct Mol Biol}, volume = {12}, number = {10}, year = {2005}, note = {McMahon, Stephen A Miller, Jason L Lawton, Jeffrey A Kerkow, Donald E Hodes, Asher Marti-Renom, Marc A Doulatov, Sergei Narayanan, Eswar Sali, Andrej Miller, Jeff F Ghosh, Partho F31AI061840/AI/NIAID NIH HHS/United States F32AI49695/AI/NIAID NIH HHS/United States T32GM008326/GM/NIGMS NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov{\textquoteright}t Research Support, U.S. Gov{\textquoteright}t, P.H.S. United States Nature structural \& molecular biology Nat Struct Mol Biol. 2005 Oct;12(10):886-92. Epub 2005 Sep 18.}, pages = {886-92}, abstract = {Only few instances are known of protein folds that tolerate massive sequence variation for the sake of binding diversity. The most extensively characterized is the immunoglobulin fold. We now add to this the C-type lectin (CLec) fold, as found in the major tropism determinant (Mtd), a retroelement-encoded receptor-binding protein of Bordetella bacteriophage. Variation in Mtd, with its approximately 10(13) possible sequences, enables phage adaptation to Bordetella spp. Mtd is an intertwined, pyramid-shaped trimer, with variable residues organized by its CLec fold into discrete receptor-binding sites. The CLec fold provides a highly static scaffold for combinatorial display of variable residues, probably reflecting a different evolutionary solution for balancing diversity against stability from that in the immunoglobulin fold. Mtd variants are biased toward the receptor pertactin, and there is evidence that the CLec fold is used broadly for sequence variation by related retroelements.}, keywords = {Amino Acid Sequence Bacterial Outer Membrane Proteins/*chemistry Bacteriophages/*metabolism Bordetella/*virology Evolution, Bordetella/*chemistry, C-Type/*chemistry Molecular Sequence Data Protein Conformation Protein Folding Viral Proteins/*chemistry/*genetics Virulence Factors, Molecular Genetic Variation Genome, Viral Lectins}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=16170324}, author = {McMahon, S. A. and Miller, J. L. and Lawton, J. A. and Kerkow, D. E. and Hodes, A. and M. A. Marti-Renom and Doulatov, S. and Narayanan, E. and Sali, A. and Miller, J. F. and Ghosh, P.} } @article {12695324, title = {Comparing bacterial genomes through conservation profiles}, journal = {Genome Res}, volume = {13}, number = {5}, year = {2003}, note = {Martin, Maria J Herrero, Javier Mateos, Alvaro Dopazo, Joaquin Comparative Study United States Genome research Genome Res. 2003 May;13(5):991-8. Epub 2003 Apr 14.}, pages = {991-8}, abstract = {We constructed two-dimensional representations of profiles of gene conservation across different genomes using the genome of Escherichia coli as a model. These profiles permit both the visualization at the genome level of different traits in the organism studied and, at the same time, reveal features related to the genomes analyzed (such as defective genomes or genomes that lack a particular system). Conserved genes are not uniformly distributed along the E. coli genome but tend to cluster together. The study of gene distribution patterns across genomes is important for the understanding of how sets of genes seem to be dependent on each other, probably having some functional link. This provides additional evidence that can be used for the elucidation of the function of unannotated genes. Clustering these patterns produces families of genes which can be arranged in a hierarchy of closeness. In this way, functions can be defined at different levels of generality depending on the level of the hierarchy that is studied. The combined study of conservation and phenotypic traits opens up the possibility of defining phenotype/genotype associations, and ultimately inferring the gene or genes responsible for a particular trait.}, keywords = {Bacterial Genotype Models, Bacterial/genetics Cluster Analysis Conserved Sequence/*genetics DNA, Bacterial/genetics Escherichia coli/classification/*genetics Evolution, Bacterial/genetics Gene Order/genetics Genes, Bacterial/genetics/physiology *Genome, Chromosome Mapping/methods Chromosomes, Genetic Phenotype Phylogeny Sequence Homology, Molecular Gene Expression Profiling/methods Gene Expression Regulation, Nucleic Acid Species Specificity Terminology as Topic}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=12695324}, author = {Martin, M. J. and Herrero, J. and A. Mateos and Dopazo, J.} } @article {11823227, title = {Calnexin overexpression increases manganese peroxidase production in Aspergillus niger}, journal = {Appl Environ Microbiol}, volume = {68}, number = {2}, year = {2002}, note = {Conesa, Ana Jeenes, David Archer, David B van den Hondel, Cees A M J J Punt, Peter J United States Applied and environmental microbiology Appl Environ Microbiol. 2002 Feb;68(2):846-51.}, pages = {846-51}, abstract = {Heme-containing peroxidases from white rot basidiomycetes, in contrast to most proteins of fungal origin, are poorly produced in industrial filamentous fungal strains. Factors limiting peroxidase production are believed to operate at the posttranslational level. In particular, insufficient availability of the prosthetic group which is required for peroxidase biosynthesis has been proposed to be an important bottleneck. In this work, we analyzed the role of two components of the secretion pathway, the chaperones calnexin and binding protein (BiP), in the production of a fungal peroxidase. Expression of the Phanerochaete chrysosporium manganese peroxidase (MnP) in Aspergillus niger resulted in an increase in the expression level of the clxA and bipA genes. In a heme-supplemented medium, where MnP was shown to be overproduced to higher levels, induction of clxA and bipA was also higher. Overexpression of these two chaperones in an MnP-producing strain was analyzed for its effect on MnP production. Whereas bipA overexpression seriously reduced MnP production, overexpression of calnexin resulted in a four- to fivefold increase in the extracellular MnP levels. However, when additional heme was provided in the culture medium, calnexin overexpression had no synergistic effect on MnP production. The possible function of these two chaperones in MnP maturation and production is discussed.}, keywords = {Aspergillus niger/*enzymology/genetics Calcium-Binding Proteins/*metabolism Calnexin Culture Media *Fungal Proteins HSP70 Heat-Shock Proteins/metabolism Heme/metabolism Peroxidases/*biosynthesis/genetics Phanerochaete/enzymology/genetics Transformation, Genetic}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=11823227}, author = {A. Conesa and Jeenes, D. and Archer, D. B. and van den Hondel, C. A. and Punt, P. J.} } @article {12645919, title = {Combining hierarchical clustering and self-organizing maps for exploratory analysis of gene expression patterns}, journal = {J Proteome Res}, volume = {1}, number = {5}, year = {2002}, note = {Herrero, Javier Dopazo, Joaquin Research Support, Non-U.S. Gov{\textquoteright}t United States Journal of proteome research J Proteome Res. 2002 Sep-Oct;1(5):467-70.}, pages = {467-70}, abstract = {Self-organizing maps (SOM) constitute an alternative to classical clustering methods because of its linear run times and superior performance to deal with noisy data. Nevertheless, the clustering obtained with SOM is dependent on the relative sizes of the clusters. Here, we show how the combination of SOM with hierarchical clustering methods constitutes an excellent tool for exploratory analysis of massive data like DNA microarray expression patterns.}, keywords = {Cluster Analysis Computational Biology/methods *Gene Expression Genes, Fungal/genetics *Genome Oligonucleotide Array Sequence Analysis/*methods Statistics as Topic/*methods Time Factors}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=12645919}, author = {Herrero, J. and Dopazo, J.} } @article {11394740, title = {Classification of protein disulphide-bridge topologies}, journal = {J Comput Aided Mol Des}, volume = {15}, number = {5}, year = {2001}, note = {Mas, J M Aloy, P Marti-Renom, M A Oliva, B de Llorens, R Aviles, F X Querol, E Comparative Study Research Support, Non-U.S. Gov{\textquoteright}t Netherlands Journal of computer-aided molecular design J Comput Aided Mol Des. 2001 May;15(5):477-87.}, pages = {477-87}, abstract = {The preferential occurrence of certain disulphide-bridge topologies in proteins has prompted us to design a method and a program, KNOT-MATCH, for their classification. The program has been applied to a database of proteins with less than 65\% homology and more than two disulphide bridges. We have investigated whether there are topological preferences that can be used to group proteins and if these can be applied to gain insight into the structural or functional relationships among them. The classification has been performed by Density Search and Hierarchical Clustering Techniques, yielding thirteen main protein classes from the superimposition and clustering process. It is noteworthy that besides the disulphide bridges, regular secondary structures and loops frequently become correctly aligned. Although the lack of significant sequence similarity among some clustered proteins precludes the easy establishment of evolutionary relationships, the program permits us to find out important structural or functional residues upon the superimposition of two protein structures apparently unrelated. The derived classification can be very useful for finding relationships among proteins which would escape detection by current sequence or topology-based analytical algorithms.}, keywords = {Algorithms Computer Simulation Databases as Topic Disulfides/*chemistry Models, Molecular Protein Structure, Secondary Protein Structure, Tertiary Proteins/*chemistry/*classification Software}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=11394740}, author = {Mas, J. M. and Aloy, P. and M. A. Marti-Renom and Oliva, B. and de Llorens, R. and Aviles, F. X. and Querol, E.} } @article {11513866, title = {C-terminal propeptide of the Caldariomyces fumago chloroperoxidase: an intramolecular chaperone?}, journal = {FEBS Lett}, volume = {503}, number = {2-3}, year = {2001}, note = {Conesa, A Weelink, G van den Hondel, C A Punt, P J Netherlands FEBS letters FEBS Lett. 2001 Aug 17;503(2-3):117-20.}, pages = {117-20}, abstract = {The Caldariomyces fumago chloroperoxidase (CPO) is synthesised as a 372-aa precursor which undergoes two proteolytic processing events: removal of a 21-aa N-terminal signal peptide and of a 52-aa C-terminal propeptide. The Aspergillus niger expression system developed for CPO was used to get insight into the function of this C-terminal propeptide. A. niger transformants expressing a CPO protein from which the C-terminal propeptide was deleted failed in producing any extracellular CPO activity, although the CPO polypeptide was synthesised. Expression of the full-length gene in an A. niger strain lacking the KEX2-like protease PclA also resulted in the production of CPO cross-reactive material into the culture medium, but no CPO activity. Based on these results, a function of the C-terminal propeptide in CPO maturation is indicated.}, keywords = {Amino Acid Sequence Ascomycota/*enzymology/genetics Aspergillus niger/genetics Base Sequence Chloride Peroxidase/biosynthesis/*chemistry/genetics DNA Primers/genetics Enzyme Precursors/biosynthesis/chemistry/genetics Gene Expression Molecular Chaperones/b}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=11513866}, author = {A. Conesa and Weelink, G. and van den Hondel, C. A. and Punt, P. J.} }