@article {728, title = {DOME: recommendations for supervised machine learning validation in biology.}, journal = {Nat Methods}, volume = {18}, year = {2021}, month = {2021 10}, pages = {1122-1127}, keywords = {Algorithms, Computational Biology, Guidelines as Topic, Humans, Models, Biological, Research Design, Supervised Machine Learning}, issn = {1548-7105}, doi = {10.1038/s41592-021-01205-4}, author = {Walsh, Ian and Fishman, Dmytro and Garcia-Gasulla, Dario and Titma, Tiina and Pollastri, Gianluca and Harrow, Jennifer and Psomopoulos, Fotis E and Tosatto, Silvio C E} } @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 {422, title = {Differential metabolic activity and discovery of therapeutic targets using summarized metabolic pathway models.}, journal = {NPJ Syst Biol Appl}, volume = {5}, year = {2019}, month = {2019}, pages = {7}, abstract = {

In spite of the increasing availability of genomic and transcriptomic data, there is still a gap between the detection of perturbations in gene expression and the understanding of their contribution to the molecular mechanisms that ultimately account for the phenotype studied. Alterations in the metabolism are behind the initiation and progression of many diseases, including cancer. The wealth of available knowledge on metabolic processes can therefore be used to derive mechanistic models that link gene expression perturbations to changes in metabolic activity that provide relevant clues on molecular mechanisms of disease and drug modes of action (MoA). In particular, pathway modules, which recapitulate the main aspects of metabolism, are especially suitable for this type of modeling. We present Metabolizer, a web-based application that offers an intuitive, easy-to-use interactive interface to analyze differences in pathway metabolic module activities that can also be used for class prediction and in silico prediction of knock-out (KO) effects. Moreover, Metabolizer can automatically predict the optimal KO intervention for restoring a diseased phenotype. We provide different types of validations of some of the predictions made by Metabolizer. Metabolizer is a web tool that allows understanding molecular mechanisms of disease or the MoA of drugs within the context of the metabolism by using gene expression measurements. In addition, this tool automatically suggests potential therapeutic targets for individualized therapeutic interventions.

}, keywords = {Computational Biology, Computer Simulation, Drug discovery, Gene Regulatory Networks, Humans, Internet, Metabolic Networks and Pathways, Models, Biological, Neoplasms, Phenotype, Software, Transcriptome}, issn = {2056-7189}, doi = {10.1038/s41540-019-0087-2}, author = {Cubuk, Cankut and Hidalgo, Marta R and Amadoz, Alicia and Rian, Kinza and Salavert, Francisco and Pujana, Miguel A and Mateo, Francesca and Herranz, Carmen and Carbonell-Caballero, Jos{\'e} and Dopazo, Joaquin} } @article {397, title = {The effects of death and post-mortem cold ischemia on human tissue transcriptomes.}, journal = {Nat Commun}, volume = {9}, year = {2018}, month = {2018 Feb 13}, pages = {490}, abstract = {

Post-mortem tissues samples are a key resource for investigating patterns of gene expression. However, the processes triggered by death and the post-mortem interval (PMI) can significantly alter physiologically normal RNA levels. We investigate the impact of PMI on gene expression using data from multiple tissues of post-mortem donors obtained from the GTEx project. We find that many genes change expression over relatively short PMIs in a tissue-specific manner, but this potentially confounding effect in a biological analysis can be minimized by taking into account appropriate covariates. By comparing ante- and post-mortem blood samples, we identify the cascade of transcriptional events triggered by death of the organism. These events do not appear to simply reflect stochastic variation resulting from mRNA degradation, but active and ongoing regulation of transcription. Finally, we develop a model to predict the time since death from the analysis of the transcriptome of a few readily accessible tissues.

}, keywords = {Blood, Cold Ischemia, Death, Female, gene expression, Humans, Models, Biological, Postmortem Changes, RNA, Messenger, Stochastic Processes, Transcriptome}, issn = {2041-1723}, doi = {10.1038/s41467-017-02772-x}, author = {Ferreira, Pedro G and Mu{\~n}oz-Aguirre, Manuel and Reverter, Ferran and S{\'a} Godinho, Caio P and Sousa, Abel and Amadoz, Alicia and Sodaei, Reza and Hidalgo, Marta R and Pervouchine, Dmitri and Carbonell-Caballero, Jos{\'e} and Nurtdinov, Ramil and Breschi, Alessandra and Amador, Raziel and Oliveira, Patr{\'\i}cia and Cubuk, Cankut and Curado, Jo{\~a}o and Aguet, Fran{\c c}ois and Oliveira, Carla and Dopazo, Joaquin and Sammeth, Michael and Ardlie, Kristin G and Guig{\'o}, Roderic} } @article {604, title = {Evidence for systems-level molecular mechanisms of tumorigenesis.}, journal = {BMC Genomics}, volume = {8}, year = {2007}, month = {2007 Jun 20}, pages = {185}, abstract = {

BACKGROUND: Cancer arises from the consecutive acquisition of genetic alterations. Increasing evidence suggests that as a consequence of these alterations, molecular interactions are reprogrammed in the context of highly connected and regulated cellular networks. Coordinated reprogramming would allow the cell to acquire the capabilities for malignant growth.

RESULTS: Here, we determine the coordinated function of cancer gene products (i.e., proteins encoded by differentially expressed genes in tumors relative to healthy tissue counterparts, hereafter referred to as "CGPs") defined as their topological properties and organization in the interactome network. We show that CGPs are central to information exchange and propagation and that they are specifically organized to promote tumorigenesis. Centrality is identified by both local (degree) and global (betweenness and closeness) measures, and systematically appears in down-regulated CGPs. Up-regulated CGPs do not consistently exhibit centrality, but both types of cancer products determine the overall integrity of the network structure. In addition to centrality, down-regulated CGPs show topological association that correlates with common biological processes and pathways involved in tumorigenesis.

CONCLUSION: Given the current limited coverage of the human interactome, this study proposes that tumorigenesis takes place in a specific and organized way at the molecular systems-level and suggests a model that comprises the precise down-regulation of groups of topologically-associated proteins involved in particular functions, orchestrated with the up-regulation of specific proteins.

}, keywords = {Cell Transformation, Neoplastic, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Humans, Male, Models, Biological, Models, Genetic, Models, Statistical, Neoplasm Proteins, Neoplasms, Prostatic Neoplasms, Protein Interaction Mapping, RNA, Messenger, Signal Transduction, Systems biology}, issn = {1471-2164}, doi = {10.1186/1471-2164-8-185}, author = {Hern{\'a}ndez, Pilar and Huerta-Cepas, Jaime and Montaner, David and Al-Shahrour, F{\'a}tima and Valls, Joan and G{\'o}mez, Laia and Capell{\`a}, Gabriel and Dopazo, Joaquin and Pujana, Miguel Angel} } @article {606, title = {From genes to functional classes in the study of biological systems.}, journal = {BMC Bioinformatics}, volume = {8}, year = {2007}, month = {2007 Apr 03}, pages = {114}, abstract = {

BACKGROUND: With the popularization of high-throughput techniques, the need for procedures that help in the biological interpretation of results has increased enormously. Recently, new procedures inspired in systems biology criteria have started to be developed.

RESULTS: Here we present FatiScan, a web-based program which implements a threshold-independent test for the functional interpretation of large-scale experiments that does not depend on the pre-selection of genes based on the multiple application of independent tests to each gene. The test implemented aims to directly test the behaviour of blocks of functionally related genes, instead of focusing on single genes. In addition, the test does not depend on the type of the data used for obtaining significance values, and consequently different types of biologically informative terms (gene ontology, pathways, functional motifs, transcription factor binding sites or regulatory sites from CisRed) can be applied to different classes of genome-scale studies. We exemplify its application in microarray gene expression, evolution and interactomics.

CONCLUSION: Methods for gene set enrichment which, in addition, are independent from the original data and experimental design constitute a promising alternative for the functional profiling of genome-scale experiments. A web server that performs the test described and other similar ones can be found at: http://www.babelomics.org.

}, keywords = {Algorithms, Chromosome Mapping, Computer Simulation, Gene Expression Profiling, Models, Biological, Multigene Family, Signal Transduction, Software, Systems biology, User-Computer Interface}, issn = {1471-2105}, doi = {10.1186/1471-2105-8-114}, author = {Al-Shahrour, F{\'a}tima and Arbiza, Leonardo and Dopazo, Hern{\'a}n and Huerta-Cepas, Jaime and Minguez, Pablo and Montaner, David and Dopazo, Joaquin} }