Machine Learning Techniques for the Automated Classification of Adhesin-Like Proteins in the Human Protozoan Parasite Trypanosoma cruzi

Machine Learning Techniques for the Automated Classification of Adhesin-Like Proteins in the Human Protozoan Parasite Trypanosoma cruzi

Autor Gonzalez, Ana M. Google Scholar
Azuaje, Francisco J. Google Scholar
Ramirez, Jose L. Google Scholar
Silveira, Jose F. da Autor UNIFESP Google Scholar
Dorronsoro, Jose R. Google Scholar
Instituição Univ Autonoma Madrid
Res Ctr Publ Hlth CRP Sante
Carretera Nacl Hoyo Puerta
Universidade Federal de São Paulo (UNIFESP)
Resumo This paper reports on the evaluation of different machine learning techniques for the automated classification of coding gene sequences obtained from several organisms in terms of their functional role as adhesins. Diverse, biologically-meaningful, sequence-based features were extracted from the sequences and used as inputs to the in silico prediction models. Another contribution of this work is the generation of potentially novel and testable predictions about the surface protein DGF-1 family in Trypanosoma cruzi. Finally, these techniques are potentially useful for the automated annotation of known adhesin-like proteins from the trans-sialidase surface protein family in T. cruzi, the etiological agent of Chagas disease.
Palavra-chave Chagas disease
adhesin-like proteins
genomic data mining
machine learning
Idioma Inglês
Financiador Spanish Ministerio de Educacion y Ciencia
FONACIT (Venezuela)
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Número do financiamento Spanish Ministerio de Educacion y Ciencia: JC2007-00148
Data de publicação 2009-10-01
Publicado em Ieee-acm Transactions On Computational Biology and Bioinformatics. Los Alamitos: Ieee Computer Soc, v. 6, n. 4, p. 695-702, 2009.
ISSN 1545-5963 (Sherpa/Romeo, fator de impacto)
Publicador Ieee Computer Soc
Extensão 695-702
Fonte http://dx.doi.org/10.1109/TCBB.2008.125
Direito de acesso Acesso restrito
Tipo Artigo
Web of Science WOS:000271163900015
Endereço permanente http://repositorio.unifesp.br/handle/11600/31873

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