Title |
Predictability of gene ontology slim-terms from primary structure information in Embryophyta plant proteins
|
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Published in |
BMC Bioinformatics, February 2013
|
DOI | 10.1186/1471-2105-14-68 |
Pubmed ID | |
Authors |
Jorge Alberto Jaramillo-Garzón, Joan Josep Gallardo-Chacón, César Germán Castellanos-Domínguez, Alexandre Perera-Lluna |
Abstract |
Proteins are the key elements on the path from genetic information to the development of life. The roles played by the different proteins are difficult to uncover experimentally as this process involves complex procedures such as genetic modifications, injection of fluorescent proteins, gene knock-out methods and others. The knowledge learned from each protein is usually annotated in databases through different methods such as the proposed by The Gene Ontology (GO) consortium. Different methods have been proposed in order to predict GO terms from primary structure information, but very few are available for large-scale functional annotation of plants, and reported success rates are much less than the reported by other non-plant predictors. This paper explores the predictability of GO annotations on proteins belonging to the Embryophyta group from a set of features extracted solely from their primary amino acid sequence. |
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