A Gene-Coexpression Network for Global Discovery of Conserved Genetic Modules

By Joshua M. Stuart, Eran Segal, Daphne Koller, Stuart K. Kim. Science, 2003

2,285 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/4a20823dd4ce6003e31f7d4e0649fe8c719926f2

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In Molecular Biology

Citations in the corpus

Key Issues in Conducting a Meta-Analysis of Gene Expression Microarray Datasets (2008, methodology): “…be used to identify genes expressed differentially between two groups [19,22,29,3 0,32,33,35,37,38,40], to robustify cross-platform classification [34], to identify overlaps between samples from heterologous datasets [30], to identify co-expressed genes, or to reconstruct gene networks [31,36,39].”
Is My Network Module Preserved and Reproducible? (2011, background): “However, previous work has shown that many co-expression modules are conserved across phylogeny [4,21,32,50], enriched with protein-protein interactions [7,21,30], and enriched with specific functional categories of genes, including ribosomal, mitochondrial, synaptic, immune, hypoxic, mitotic, and m”
Gene regulatory network inference: Data integration in dynamic models - A review (2009, background): “One of the simplest network architectures is the correlation network (Stuart et al., 2003), which can be represented by an undirected graph with edges that are weighted by correlation coefficients.”
ATTED-II provides coexpressed gene networks for Arabidopsis (2008, background): “Such ‘conserved coexpression’, as we call it here, can predict gene-to-gene functional relationships more accurately because their coexpression has been conserved across evolution ( 17 ).”
Ensembles for feature selection: A review and future trends (2019, neutral): “For example, Stuart et al. [44] introduced the (cid:12)rst attempt to use order statistics in the combination of rankings, although the computational scheme for their method was further optimized by Aerts et al. [45].”
Approaches for extracting practical information from gene co-expression networks in plant biology. (2007, methodology): “…modules is evaluated by statistical tests based on random resampling (Lisso et al. 2005, Wei et al. 2006) or permutation (shuffling of the data to create pseudo data sets) (Stuart et al. 2003), and the results are interpreted using biological knowledge such as annotation and pathway information.”
Scaling Laws in the Functional Content of Genomes (2003, background): “This holds both when one defines ’interaction’ between genes on the level of the proteins that they encode [17, 9, 14] or if one defines it at the level of co-regula tion of the expression of the genes [16].”
Computational tools for prioritizing candidate genes: boosting disease gene discovery (2012, background): “Data are highly heterogeneous (for example, sequence, expression, PPIs, annotation and literature) and lead to various relevant relations that can be detected between genes: sequence homology, co-expression 40 , PPIs 20,41 , shared functional annotations or co-occurrence in literature abstracts 42 .”