Molecular signatures database (MSigDB) 3.0

By Arthur Liberzon, Aravind Subramanian, Reid Pinchback, Helga Thorvaldsdóttir, Pablo Tamayo, Jill P. Mesirov. 2011

6,262 citations recorded by the source corpus.

Subfields: Molecular Biology, Computational Biology & Bioinformatics

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Citations in the corpus

Comparative genetic architectures of schizophrenia in East Asian and European populations (2018, neutral): “Seventy gene-sets were selected and tested in this study (Supplementary Table 8), including those from the Molecular Signatures Database 76 , related to psychiatric diseases 38,77,78 and from ‘gwaspipeline’(https://github.com/freeseek/gwaspipeline/blob/ master/makegenes.sh).”
The Short Chain Fatty Acid Butyrate Imprints an Antimicrobial Program in Macrophages (2019, methodology): “Gene set enrichment analysis (Figure 3E) was performed using Fisher’s Exact Test (FET), Biological Process gene sets obtained from Gene Ontology (GO) databases (Ashburner et al., 2000; Kanehisa and Goto, 2000; Liberzon et al., 2011; Subramanian et al., 2005), and a gene universe that comprised of ge”
Systematic integration of biomedical knowledge prioritizes drugs for repurposing (2017, background): “However, we did voluntarily remove MSigDB ( Liberzon et al., 2011 ), since its license was highly problematic ( Himmelstein, 2015d ).”
pathfindR: An R Package for Comprehensive Identification of Enriched Pathways in Omics Data Through Active Subnetworks (2019, methodology): “BioCarta gene sets in GMT format were retrieved from the Molecular Signatures Database (MSigDB) (Liberzon et al., 2011) website (http://software. broadinstitute.org/gsea/msigdb).”
Genomic basis for RNA alterations in cancer (2020, methodology): “The splicing related genes were derived from the genes annotated as ‘REACTOME_MRNA_SPLICING’ or ‘REACTOME_MRNA_SPLICING_MINOR_PATHWAY’ in the Molecular Signatures Database (MSigDB) 116 .”
Enrichr: a comprehensive gene set enrichment analysis web server 2016 update (2016, background): “Later on, other types of annotated gene sets for enrichment analysis emerged; for example, chromosome location of genes, computationally predicted targets of microRNAs and transcription factors, and gene modules identified computationally from large collections of gene expression data (6).”
GeneMANIA Prediction Server 2013 Update (2013, methodology): “We currently only use attributes derived from InterPro domains, although we intend to expand our attribute sets in the near future to include, for example, gene attributes deﬁned by mSigDB (16).”