A module map showing conditional activity of expression modules in cancer

By Eran Segal, Nir Friedman, Daphne Koller, Aviv Regev. Nature Genetics, 2004

750 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/a7d4127432b13b5c1deade3e85b5f461838ecdf2

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Citations in the corpus

Pathway-based personalized analysis of cancer (2013, background): “Nevertheless, such scores were calculated by Segal et al. as interim results, derived by counting the number of signi ﬁ cantly up-and down-regulated genes and performing gene set enrichment analysis (separately for the two gene groups),assigningscoresof ± 1or0toeachpathwayandsample.”
Exploiting drug-disease relationships for computational drug repositioning (2011, neutral): “[39–41].”
Protein Networks as Logic Functions in Development and Cancer (2011, background): “major activity within the field of Systems Biology has been to identify such modules systematically through analysis of global data sets [12–16].”
Local Multidimensional Scaling with Controlled Tradeoff Between Trustworthiness and Continuity (2005, neutral): “[9].”
Integrative analysis of the cancer transcriptome (2005, background): “A recent study took systematic functional analysis a step further by analyzing hundreds of gene sets in the context of a compendium of diverse cancer profile”
Comprehensive literature review and statistical considerations for microarray meta-analysis (2012, background): “(21) was probably the first large-scale microarray meta-analysis for network or co-expression analysis.”
From signatures to models: understanding cancer using microarrays (2005, methodology): “To transcend from individual genes to biological processes, several recent methods 7–10 use gene modules as the basic building blocks for analysis.”
Systematic survey reveals general applicability of "guilt-by-association" within gene coexpression networks (2005, background): “By exploiting the insight that subtle but coordinated changes in expression can be detected by combining measurements across multiple members of a functional module, these focused studies have successfully found specific modules that are important in diabetes [12], aging [13], and cancer [10,11,14,1”
An expression atlas of human primary cells: inference of gene function from coexpression networks (2013, background): “lable for identifying clusters or modules of coexpressed genes within expression data [20-25].”
A modular analysis framework for blood genomics studies: application to systemic lupus erythematosus (2008, background): “Among those, approaches to uncover the modular organization and function of transcriptional systems have already shown promise (Mootha et al., 2003; Rhodes et al., 2005; Segal et al., 2004; reviewed in Segal et al., 2005).”
An embryonic stem cell–like gene expression signature in poorly differentiated aggressive human tumors (2008, methodology): “Here, we use recently developed gene set expression analysis method”
Module map of stem cell genes guides creation of epithelial cancer stem cells. (2008, methodology): “Gene Module Map Gene module map was implemented with the program Genomica (Segal et al., 2004).”