FunSpec: a web-based cluster interpreter for yeast

By Mark D. Robinson, Jörg Grigull, Naveed Mohammad, Timothy R. Hughes. BMC Bioinformatics, 2002

448 citations recorded by the source corpus.

BackgroundFor effective exposition of biological information, especially with regard to analysis of large-scale data types, researchers need immediate access to multiple categorical knowledge bases and need summary information presented to them on collections of genes, as opposed to the typical one gene at a time.ResultsWe present here a web-based tool (FunSpec) for statistical evaluation of groups of genes and proteins (e.g. co-regulated genes, protein complexes, genetic interactors) with respect to existing annotations (e.g. functional roles, biochemical properties, localization). FunSpec is available online at http://funspec.med.utoronto.caConclusionFunSpec is helpful for interpretation of any data type that generates groups of related genes and proteins, such as gene expression clustering and protein complexes, and is useful for predictive methods employing "guilt-by-association."

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/a5e3bcf2d7fdb94729f5d6a3c0f3f4a3fc0bf391

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Citations in the corpus

Enrichment or depletion of a GO category within a class of genes: which test? (2007, background): “We consider successively the hypergeometric, the comparison of two probabilities, and the 2 · 2 contingency table formulations of the above problem, and introduce the exact or approximate null distributions they lead to.”
FatiGO: a web tool for finding significant associations of Gene Ontology terms with groups of genes (2004, methodology): “A similar tool, FunSpec (Robinson et al., 2002), evaluates groups of yeast genes in terms of their annotations in diverse databases.”
GOToolBox: functional analysis of gene datasets based on Gene Ontology (2004, methodology): “FuncSpec [ 21 ] Hypergeometric Bonferroni TAB/RANK ALL”
GOEAST: a web-based software toolkit for Gene Ontology enrichment analysis (2008, methodology): “To circumvent the multi-test problem which might induce too much false positive results, GOEAST by default adjusts the raw P-values into false discovery rate (FDR) using the Benjamini–Yekutieli method (30).”
Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation (2007, background): “These minimal medium–induced proteins are statistically significantly enriched for proteins of metabolism ( P −14 ; 70 proteins) and biosynthesis ( P −14 ; 36 proteins”
GO: : TermFinder--open source software for accessing Gene Ontology information and finding significantly enriched Gene Ontology terms associated with a list of genes (2004, methodology): “These include FunSpec (Robinson et al., 2002), Onto-Express (Draghici et al.”
Enrichment Map: A Network-Based Method for Gene-Set Enrichment Visualization and Interpretation (2010, background): “Most enrichment tools derive gene-sets from Gene Ontology (GO) annotations [11], because they are readily accessible for many organisms and cover many genes, yet many other sources of genesets exist and are used by some tools in addition to GO [7,12,13].”