A multi-objective optimization approach accurately resolves protein domain architectures

Autor: Bernardes, Juliana Silva, Rocha Jimenez Vieira, Fabio, Zaverucha, G., Carbone, Alessandra
Přispěvatelé: Biologie Computationnelle et Quantitative = Laboratory of Computational and Quantitative Biology (LCQB), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut de Biologie Paris Seine (IBPS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Networks and Performance Analysis (NPA), Laboratoire d'Informatique de Paris 6 (LIP6), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Programa de Engenharia de Sistemas e Computação (PESC), Universidade Federal do Rio de Janeiro (UFRJ), Institut Universitaire de France (IUF), Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche (M.E.N.E.S.R.), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)
Jazyk: angličtina
Rok vydání: 2015
Předmět:
Zdroj: Bioinformatics
Bioinformatics, Oxford University Press (OUP), 2015, 32 (3), pp.345-353. ⟨10.1093/bioinformatics/btv582⟩
Bioinformatics, 2015, 32 (3), pp.345-353. ⟨10.1093/bioinformatics/btv582⟩
ISSN: 1367-4803
1367-4811
DOI: 10.1093/bioinformatics/btv582⟩
Popis: International audience; Motivation: Given a protein sequence and a number of potential domains matching it, what are the domain content and the most likely domain architecture for the sequence? This problem is of fundamental importance in protein annotation, constituting one of the main steps of all predictive annotation strategies. On the other hand, when potential domains are several and in conflict because of overlapping domain boundaries, finding a solution for the problem might become difficult. An accurate prediction of the domain architecture of a multi-domain protein provides important information for function prediction, comparative genomics and molecular evolution. Results: We developed DAMA (Domain Annotation by a Multi-objective Approach), a novel approach that identifies architectures through a multi-objective optimization algorithm combining scores of domain matches, previously observed multi-domain co-occurrence and domain overlapping. DAMA has been validated on a known benchmark dataset based on CATH structural domain assignments and on the set of Plasmodium falciparum proteins. When compared with existing tools on both datasets, it outperforms all of them. Availability and implementation: DAMA software is implemented in Cþþ and the source code can be found at
Databáze: OpenAIRE
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