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INGA: protein function prediction combining interaction networks, domain assignments and sequence similarity
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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4489281/ https://www.ncbi.nlm.nih.gov/pubmed/26019177 http://dx.doi.org/10.1093/nar/gkv523 |
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author | Piovesan, Damiano Giollo, Manuel Leonardi, Emanuela Ferrari, Carlo Tosatto, Silvio C.E. |
author_facet | Piovesan, Damiano Giollo, Manuel Leonardi, Emanuela Ferrari, Carlo Tosatto, Silvio C.E. |
author_sort | Piovesan, Damiano |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4489281 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-44892812015-07-07 INGA: protein function prediction combining interaction networks, domain assignments and sequence similarity Piovesan, Damiano Giollo, Manuel Leonardi, Emanuela Ferrari, Carlo Tosatto, Silvio C.E. Nucleic Acids Res Web Server issue 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. Oxford University Press 2015-07-01 2015-05-27 /pmc/articles/PMC4489281/ /pubmed/26019177 http://dx.doi.org/10.1093/nar/gkv523 Text en © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Web Server issue Piovesan, Damiano Giollo, Manuel Leonardi, Emanuela Ferrari, Carlo Tosatto, Silvio C.E. INGA: protein function prediction combining interaction networks, domain assignments and sequence similarity |
title | INGA: protein function prediction combining interaction networks, domain assignments and sequence similarity |
title_full | INGA: protein function prediction combining interaction networks, domain assignments and sequence similarity |
title_fullStr | INGA: protein function prediction combining interaction networks, domain assignments and sequence similarity |
title_full_unstemmed | INGA: protein function prediction combining interaction networks, domain assignments and sequence similarity |
title_short | INGA: protein function prediction combining interaction networks, domain assignments and sequence similarity |
title_sort | inga: protein function prediction combining interaction networks, domain assignments and sequence similarity |
topic | Web Server issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4489281/ https://www.ncbi.nlm.nih.gov/pubmed/26019177 http://dx.doi.org/10.1093/nar/gkv523 |
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