FatiGO: a web tool for finding significant associations of Gene ontology terms with groups of genes. Summary: We present a simple but powerful procedure to extract Gene Ontology (GO) terms that are significantly over- or under-represented in sets of genes within the context of a genome-scale experiment (DNA microarray, proteomics, etc.). Said procedure has been implemented as a web application, FatiGO, allowing for easy and interactive querying. FatiGO, which takes the multiple-testing nature of statistical contrast into account, currently includes GO associations for diverse organisms (human, mouse, fly, worm and yeast) and the TrEMBL/Swissprot GOAnnotations@EBI correspondences from the European Bioinformatics Institute. Availability: http://fatigo.bioinfo.cnio.es

References in zbMATH (referenced in 11 articles )

Showing results 1 to 11 of 11.
Sorted by year (citations)

  1. Zimek, Arthur; Vreeken, Jilles: The blind men and the elephant: on meeting the problem of multiple truths in data from clustering and pattern mining perspectives (2015)
  2. Drăghici, Sorin: Statistics and data analysis for microarrays using R and Bioconductor. With CD-ROM. (2012)
  3. Maulik, Ujjwal; Bandyopadhyay, Sanghamitra; Mukhopadhyay, Anirban: Multiobjective genetic algorithms for clustering. Applications in data mining and bioinformatics. (2011)
  4. Jupiter, Daniel; Şahutoğlu, Jessica; Vanburen, Vincent: TreeHugger: a new test for enrichment of gene ontology terms (2010)
  5. Newton, Michael A.; Quintana, Fernando A.; Den Boon, Johan A.; Sengupta, Srikumar; Ahlquist, Paul: Random-set methods identify distinct aspects of the enrichment signal in gene-set analysis (2007)
  6. Sánchez, Alex; Salicrú, Miquel; Ocaña, Jordi: Statistical methods for the analysis of high-throughput data based on functional profiles derived from the Gene Ontology (2007)
  7. Chen, Chin-Fu; Feng, Xin; Szeto, Jack: Identification of critical genes in microarray experiments by a neuro-fuzzy approach (2006)
  8. Lewin, Alex; Richardson, Sylvia; Marshall, Clare; Glazier, Anne; Aitman, Tim: Bayesian modeling of differential gene expression (2006)
  9. Pan, Wei: Incorporating biological information as a prior in an empirical Bayes approach to analyzing microarray data (2005)
  10. Lambrix, Patrick: Ontologies in bioinformatics and systems biology (2004)
  11. Rahnenführer, Jörg; Domingues, Francisco S.; Maydt, Jochen; Lengauer, Thomas: Calculating the statistical significance of changes in pathway activity from gene expression data (2004)