FatiGO +: a functional profiling tool for genomic data. Integration of functional annotation, regulatory motifs and interaction data with microarray experiments.
The ultimate goal of any genome-scale experiment is to provide a functional interpretation of the data, relating the available information with the hypotheses that originated the experiment. Thus, functional profiling methods have become essential in diverse scenarios such as microarray experiments, proteomics, etc. We present the FatiGO+, a web-based tool for the functional profiling of genome-scale experiments, specially oriented to the interpretation of microarray experiments. In addition to different functional annotations (gene ontology, KEGG pathways, Interpro motifs, Swissprot keywords and text-mining based bioentities related to diseases and chemical compounds) FatiGO+ includes, as a novelty, regulatory and structural information. The regulatory information used includes predictions of targets for distinct regulatory elements (obtained from the Transfac and CisRed databases). Additionally FatiGO+ uses predictions of target motifs of miRNA to infer which of these can be activated or deactivated in the sample of genes studied. Finally, properties of gene products related to their relative location and connections in the interactome have also been used. Also, enrichment of any of these functional terms can be directly analysed on chromosomal coordinates. FatiGO+ can be found at: http://www.fatigoplus.org and within the Babelomics environment http://www.babelomics.org.
Al-Shahrour
Fátima
F
Bioinformatics Department, Centro de Investigación Príncipe Felipe (CIPF), Valencia 46013, Spain.
Minguez
Pablo
P
Tárraga
Joaquín
J
Medina
Ignacio
I
Alloza
Eva
E
Montaner
David
D
Dopazo
Joaquín
J
D020816:Amino Acid Motifs; D000818:Animals; D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D020869:Gene Expression Profiling; D005796:Genes; D023281:Genomics / Q000379:methods*; D006801:Humans; D020407:Internet; D020411:Oligonucleotide Array Sequence Analysis; D011381:Programming Languages; D012984:Software; D018511:Systems Integration; D014157:Transcription Factors / Q000378:metabolism
D014157:Transcription Factors