ArticleBMC bioinformatics2006
GOFFA: gene ontology for functional analysis--a FDA gene ontology tool for analysis of genomic and proteomic data.
Article in BMC bioinformatics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- Fifteen Years of Gene Set Analysis for High-Throughput Genomic Data: A Review of Statistical Approaches and Future Challenges.Entropy (Basel, Switzerland) · 2020Review
- Dietary supplementation with long-chain monounsaturated fatty acid isomers decreases atherosclerosis and alters lipoprotein proteomes in LDLrAtherosclerosis · 2017Article
- Castration Resistance in Prostate Cancer Is Mediated by the Kinase NEK6.Cancer research · 2017Article
- Identification and Characterization of miRNAs in Chondrus crispus by High-Throughput Sequencing and Bioinformatics Analysis.Scientific reports · 2016Article
- Coordinated Action of Biological Processes during Embryogenesis Can Cause Genome-Wide Linkage Disequilibrium in the Human Genome and Influence Age-Related Phenotypes.Annals of gerontology and geriatric research · 2016Article
- Effects of oral exposure to bisphenol A on gene expression and global genomic DNA methylation in the prostate, female mammary gland, and uterus of NCTR Sprague-Dawley rats.Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association · 2015Article
- Activated FoxM1 attenuates streptozotocin-mediated β-cell death.Molecular endocrinology (Baltimore, Md.) · 2014Article
- HACE1-dependent protein degradation provides cardiac protection in response to haemodynamic stress.Nature communications · 2014Article
- Genomics of human health and aging.Age (Dordrecht, Netherlands) · 2013Article
- Ten years of pathway analysis: current approaches and outstanding challenges.PLoS computational biology · 2012Review
- Genomic differences distinguish the myofibroblast phenotype of distal lung fibroblasts from airway fibroblasts.American journal of respiratory cell and molecular biology · 2011Article
- Identification of an FHL1 protein complex containing ACTN1, ACTN4, and PDLIM1 using affinity purifications and MS-based protein-protein interaction analysis.Molecular bioSystems · 2011Article
- Ketamine-induced neurotoxicity and changes in gene expression in the developing rat brain.Current neuropharmacology · 2011Article
- Article
- Identification of New SRF Binding Sites in Genes Modulated by SRF Over-Expression in Mouse Hearts.Gene regulation and systems biology · 2011Article
- An FDA bioinformatics tool for microbial genomics research on molecular characterization of bacterial foodborne pathogens using microarrays.BMC bioinformatics · 2010Article
- ArrayTrack: a free FDA bioinformatics tool to support emerging biomedical research--an update.Human genomics · 2010Review
- Gene expression profiling in the developing rat brain exposed to ketamine.Neuroscience · 2010Article
- Gene expression profiling of the proliferative effect of periplocin on mouse cardiac microvascular endothelial cells.Chinese journal of integrative medicine · 2010Article
- Gene-disease relationship discovery based on model-driven data integration and database view definition.Bioinformatics (Oxford, England) · 2009Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGene Ontology (GO) characterizes and categorizes the functions of genes and their products according to biological processes, molecular functions and cellular components, facilitating interpretation of data from high-throughput genomics and proteomics technologies. The most effective use of GO information is achieved when its rich and hierarchical complexity is retained and the information is distilled to the biological functions that are most germane to the phenomenon being investigated.
resultsHere we present a FDA GO tool named Gene Ontology for Functional Analysis (GOFFA). GOFFA first ranks GO terms in the order of prevalence for a list of selected genes or proteins, and then it allows the user to interactively select GO terms according to their significance and specific biological complexity within the hierarchical structure. GOFFA provides five interactive functions (Tree view, Terms View, Genes View, GO Path and GO TreePrune) to analyze the GO data. Among the five functions, GO Path and GO TreePrune are unique. The GO Path simultaneously displays the ranks that order GOFFA Tree Paths based on statistical analysis. The GO TreePrune provides a visual display of a reduced GO term set based on a user's statistical cut-offs. Therefore, the GOFFA visual display can provide an intuitive depiction of the most likely relevant biological functions.
conclusionWith GOFFA, the user can dynamically interact with the GO data to interpret gene expression results in the context of biological plausibility, which can lead to new discoveries or identify new hypotheses. AVAILABILITY: GOFFA is available through ArrayTrack softwarehttp://edkb.fda.gov/webstart/arraytrack/.
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