MiRvestigator: Web application to identify miRNAs responsible for co-regulated gene expression patterns discovered through transcriptome profiling

Christopher L. Plaisier, J. Christopher Bare, Nitin S. Baliga

Research output: Contribution to journalArticle

25 Scopus citations

Abstract

Transcriptome profiling studies have produced staggering numbers of gene co-expression signatures for a variety of biological systems. A significant fraction of these signatures will be partially or fully explained by miRNA-mediated targeted transcript degradation. miRvestigator takes as input lists of co-expressed genes from Caenorhabditis elegans, Drosophila melanogaster, G. gallus, Homo sapiens, Mus musculus or Rattus norvegicus and identifies the specific miRNAs that are likely to bind to 3′ un-translated region (UTR) sequences to mediate the observed co-regulation. The novelty of our approach is the miRvestigator hidden Markov model (HMM) algorithm which systematically computes a similarity P-value for each unique miRNA seed sequence from the miRNA database miRBase to an overrepresented sequence motif identified within the 3′-UTR of the query genes. We have made this miRNA discovery tool accessible to the community by integrating our HMM algorithm with a proven algorithm for de novo discovery of miRNA seed sequences and wrapping these algorithms into a user-friendly interface. Additionally, the miRvestigator web server also produces a list of putative miRNA binding sites within 3′-UTRs of the query transcripts to facilitate the design of validation experiments. The miRvestigator is freely available at http://mirvestigator.systemsbiology. net.

Original languageEnglish (US)
Pages (from-to)W125-W131
JournalNucleic acids research
Volume39
Issue numberSUPPL. 2
DOIs
StatePublished - Jul 1 2011
Externally publishedYes

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ASJC Scopus subject areas

  • Genetics

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