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GOTA: GO term annotation of biomedical literature

BACKGROUND: Functional annotation of genes and gene products is a major challenge in the post-genomic era. Nowadays, gene function curation is largely based on manual assignment of Gene Ontology (GO) annotations to genes by using published literature. The annotation task is extremely time-consuming,...

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Autores principales: Lena, Pietro Di, Domeniconi, Giacomo, Margara, Luciano, Moro, Gianluca
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4625458/
https://www.ncbi.nlm.nih.gov/pubmed/26511083
http://dx.doi.org/10.1186/s12859-015-0777-8
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author Lena, Pietro Di
Domeniconi, Giacomo
Margara, Luciano
Moro, Gianluca
author_facet Lena, Pietro Di
Domeniconi, Giacomo
Margara, Luciano
Moro, Gianluca
author_sort Lena, Pietro Di
collection PubMed
description BACKGROUND: Functional annotation of genes and gene products is a major challenge in the post-genomic era. Nowadays, gene function curation is largely based on manual assignment of Gene Ontology (GO) annotations to genes by using published literature. The annotation task is extremely time-consuming, therefore there is an increasing interest in automated tools that can assist human experts. RESULTS: Here we introduce GOTA, a GO term annotator for biomedical literature. The proposed approach makes use only of information that is readily available from public repositories and it is easily expandable to handle novel sources of information. We assess the classification capabilities of GOTA on a large benchmark set of publications. The overall performances are encouraging in comparison to the state of the art in multi-label classification over large taxonomies. Furthermore, the experimental tests provide some interesting insights into the potential improvement of automated annotation tools. CONCLUSIONS: GOTA implements a flexible and expandable model for GO annotation of biomedical literature. The current version of the GOTA tool is freely available at http://gota.apice.unibo.it. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0777-8) contains supplementary material, which is available to authorized users.
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spelling pubmed-46254582015-10-30 GOTA: GO term annotation of biomedical literature Lena, Pietro Di Domeniconi, Giacomo Margara, Luciano Moro, Gianluca BMC Bioinformatics Methodology Article BACKGROUND: Functional annotation of genes and gene products is a major challenge in the post-genomic era. Nowadays, gene function curation is largely based on manual assignment of Gene Ontology (GO) annotations to genes by using published literature. The annotation task is extremely time-consuming, therefore there is an increasing interest in automated tools that can assist human experts. RESULTS: Here we introduce GOTA, a GO term annotator for biomedical literature. The proposed approach makes use only of information that is readily available from public repositories and it is easily expandable to handle novel sources of information. We assess the classification capabilities of GOTA on a large benchmark set of publications. The overall performances are encouraging in comparison to the state of the art in multi-label classification over large taxonomies. Furthermore, the experimental tests provide some interesting insights into the potential improvement of automated annotation tools. CONCLUSIONS: GOTA implements a flexible and expandable model for GO annotation of biomedical literature. The current version of the GOTA tool is freely available at http://gota.apice.unibo.it. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0777-8) contains supplementary material, which is available to authorized users. BioMed Central 2015-10-28 /pmc/articles/PMC4625458/ /pubmed/26511083 http://dx.doi.org/10.1186/s12859-015-0777-8 Text en © Di Lena et al. 2015 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology Article
Lena, Pietro Di
Domeniconi, Giacomo
Margara, Luciano
Moro, Gianluca
GOTA: GO term annotation of biomedical literature
title GOTA: GO term annotation of biomedical literature
title_full GOTA: GO term annotation of biomedical literature
title_fullStr GOTA: GO term annotation of biomedical literature
title_full_unstemmed GOTA: GO term annotation of biomedical literature
title_short GOTA: GO term annotation of biomedical literature
title_sort gota: go term annotation of biomedical literature
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4625458/
https://www.ncbi.nlm.nih.gov/pubmed/26511083
http://dx.doi.org/10.1186/s12859-015-0777-8
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