@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 {712, title = {A versatile workflow to integrate RNA-seq genomic and transcriptomic data into mechanistic models of signaling pathways.}, journal = {PLoS Comput Biol}, volume = {17}, year = {2021}, month = {2021 02}, pages = {e1008748}, abstract = {

MIGNON is a workflow for the analysis of RNA-Seq experiments, which not only efficiently manages the estimation of gene expression levels from raw sequencing reads, but also calls genomic variants present in the transcripts analyzed. Moreover, this is the first workflow that provides a framework for the integration of transcriptomic and genomic data based on a mechanistic model of signaling pathway activities that allows a detailed biological interpretation of the results, including a comprehensive functional profiling of cell activity. MIGNON covers the whole process, from reads to signaling circuit activity estimations, using state-of-the-art tools, it is easy to use and it is deployable in different computational environments, allowing an optimized use of the resources available.

}, keywords = {Algorithms, Cell Line, Tumor, Computational Biology, Databases, Factual, Gene Expression Profiling, Genomics, High-Throughput Nucleotide Sequencing, Humans, Models, Theoretical, mutation, RNA-seq, Signal Transduction, Software, Transcriptome, whole exome sequencing, Workflow}, issn = {1553-7358}, doi = {10.1371/journal.pcbi.1008748}, author = {Garrido-Rodriguez, Mart{\'\i}n and L{\'o}pez-L{\'o}pez, Daniel and Ortuno, Francisco M and Pe{\~n}a-Chilet, Maria and Mu{\~n}oz, Eduardo and Calzado, Marco A and Dopazo, Joaquin} }