Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists

By Danzhi Huang, Brad T. Sherman, Richard A. Lempicki. 2008

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Citations in the corpus

Ten Years of Pathway Analysis: Current Approaches and Outstanding Challenges (2012, methodology): “We refer the readers to recent comparisons of ORA tools for more details [12,13].”
A survey of best practices for RNA-seq data analysis (2016, background): “Resources such as Gene Ontology [109], Bioconductor [110], DAVID [111, 112] or Babelomics [113] contain annotation data for most model species.”
Pattern discovery and cancer gene identification in integrated cancer genomic data (2013, methodology): “Functional annotation analysis of the differentially expressed genes using DAVID (28) revealed tissue-speci ﬁ c biological processes, including lymphocyte differentiation in clusters 2 and 3, mammary gland development in cluster 4, and neuron differentiation in cluster 7.”
NOA: a novel Network Ontology Analysis method (2011, background): “Recently, Huang et al. (2) comprehensively reviewed 68 bioinformatics enrichment tools and classiﬁed them into three classes: singular enrichment analysis, gene set enrichment analysis and modular enrichment analysis.”
Lysine Glutarylation Is a Protein Post-Translational Modification Regulated by SIRT5 (2014, methodology): “Bioinformatic Analyses of Kglu Substrates To identify the possible association of Kglu substrates with cellular functions, we carried out gene ontology (GO) enrichment analysis using DAVID bioinformatics resources (Huang et al., 2009).”
Multidimensional proteomics for cell biology (2015, background): “Although these data are rich and each association is strongly supported by statistical evidence, there is still a need to improve built-in visualization tools for the data output of DAVID.”
Identification of fever and vaccine-associated gene interaction networks using ontology-based literature mining (2012, methodology): “The Database for Annotation, Visualization and Integrated Discovery (DAVID) (Huang da, et al., 2009) was employed to identify over-represented biological functions and pathways between the genes in the fever-and vaccine-associated fever networks.”