Gene co-expression network topology provides a framework for molecular characterization of cellular state

By Scott L. Carter, Christian M. Brechbühler, Michael Griffin, Andrew T. Bond. Bioinform., 2004

355 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/4116adb2fad723ff1f5f2fe555df22087beb58ee

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In Molecular Biology

Citations in the corpus

Eigengene networks for studying the relationships between co-expression modules (2007, background): “Several recent works have described differential network analysis methods for gene co-expression networks [11-13].”
Gene connectivity, function, and sequence conservation: predictions from modular yeast co-expression networks (2006, background): “Both of these network types have been frequently observed as having a scale-free topology, with the existence of highly connected hub nodes [ 3-7 ].”
MIENTURNET: an interactive web tool for microRNA-target enrichment and network-based analysis (2019, background): “2c), consistent with how emerged so far in almost all biological networks [30–32].”
Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015, background): “For gene expression studies, co-expression network analysis leverages the fact that gene expression reflects the state of the cellular or tissue system that is being analysed 25 .”
Global Testing and Large-Scale Multiple Testing for High-Dimensional Covariance Structures (2017, background): “There are a wide array of applications, including brain connectivity analysis (Shaw et al. 2006), gene co-expression network analysis (Carter et al. 2004; Lee et al. 2004; Zhang et al. 2008; Dubois et al. 2010; Fuller et al. 2007), differential gene expression analysis (Shedden and Taylor (2005);…”
Analysis of global control of Escherichia coli carbohydrate uptake (2007, neutral): “Connectivity has been found to be an important complementary gene screening variable for finding biologically significant genes in cancer [10,11] and primate brain development [12].”
Statistical Estimation of Correlated Genome Associations to a Quantitative Trait Network (2009, methodology): “This thresholded correlation graph is also known as a relevance network, and has been widely used as a representation of gene interaction networks [29, 30 ].”