Babelomics: an integrative platform for the analysis of transcriptomics, proteomics and genomic data with advanced functional profiling

By Ignacio Medina, J. Carbonell, Luis Pulido, Sara Cordeiro Madeira, Stefan Götz, Ana Conesa, Joaquín Tárraga, Alberto Domingo Pascual-Montano, Rubén Nogales-Cadenas, J. Santoyo and 4 more. Nucleic Acids Res., 2010

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Babelomics is a response to the growing necessity of integrating and analyzing different types of genomic data in an environment that allows an easy functional interpretation of the results. Babelomics includes a complete suite of methods for the analysis of gene expression data that include normalization (covering most commercial platforms), pre-processing, differential gene expression (case-controls, multiclass, survival or continuous values), predictors, clustering; large-scale genotyping assays (case controls and TDTs, and allows population stratification analysis and correction). All these genomic data analysis facilities are integrated and connected to multiple options for the functional interpretation of the experiments. Different methods of functional enrichment or gene set enrichment can be used to understand the functional basis of the experiment analyzed. Many sources of biological information, which include functional (GO, KEGG, Biocarta, Reactome, etc.), regulatory (Transfac, Jaspar, ORegAnno, miRNAs, etc.), text-mining or protein–protein interaction modules can be used for this purpose. Finally a tool for the de novo functional annotation of sequences has been included in the system. This provides support for the functional analysis of non-model species. Mirrors of Babelomics or command line execution of their individual components are now possible. Babelomics is available at http://www.babelomics.org.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/917d15fb3b71a3925b467af8b98bb37643a6fbe2

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In Molecular Biology

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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.”