Literature DB >> 26019177

INGA: protein function prediction combining interaction networks, domain assignments and sequence similarity.

Damiano Piovesan1, Manuel Giollo2, Emanuela Leonardi3, Carlo Ferrari4, Silvio C E Tosatto5.   

Abstract

Identifying protein functions can be useful for numerous applications in biology. The prediction of gene ontology (GO) functional terms from sequence remains however a challenging task, as shown by the recent CAFA experiments. Here we present INGA, a web server developed to predict protein function from a combination of three orthogonal approaches. Sequence similarity and domain architecture searches are combined with protein-protein interaction network data to derive consensus predictions for GO terms using functional enrichment. The INGA server can be queried both programmatically through RESTful services and through a web interface designed for usability. The latter provides output supporting the GO term predictions with the annotating sequences. INGA is validated on the CAFA-1 data set and was recently shown to perform consistently well in the CAFA-2 blind test. The INGA web server is available from URL: http://protein.bio.unipd.it/inga.
© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

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Year:  2015        PMID: 26019177      PMCID: PMC4489281          DOI: 10.1093/nar/gkv523

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  32 in total

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