Remote-3DD : A New Remote Homology Detection Method that uses Physicochemical Properties.

(Eng) This article presents a new method for remote peer detection, called remote-3DD, which combines predicted contact maps and a distribution of the values ​​in the interaction matrices. The predicted contact maps are an approximation of the 3D shape of protein that can be obtained from its primary structure. For its part, an interaction matrix makes it possible to represent a protein from the physicochemical properties of the amino acids that make it up. Remote-3DD is proposed as a strategy to improve the accuracy of the remote-C3D method in which only contact maps are used. The hypothesis in this article is that the accuracy of the remote-C3D method can be improved by incorporating the distributions of the interaction matrix. The test results show that the remote-3DD method achieves higher accuracy than composition-based methods and in some cases comparable accuracy with profile-based methods. In addition, the tests show that the remote-3DD method, in general, exhibits higher accuracies than the remote-C3D method when using the same number of models and sub-matrix sizes.

• Autores: Oscar Fernando Bedoya Leiva
• Tipo de recurso: Article of journal
• Fecha de publicación: 2017
• Institución: Universidad del Valle
• Repositorio: Repositorio Digital Univalle
• Idioma: eng
• OAI Identifier: oai:bibliotecadigital.univalle.edu.co:10893/18145
• Acceso en línea: https://hdl.handle.net/10893/18145
• Palabra clave: Bioinformatica; Clasificadores; Conjunto de datos SCOP; Homólogos remotos; Propiedades fisicoquímicas; Bioinformatics; Classifiers; SCOP data set; Remote homologs; Physicochemical properties
• Rights: closedAccess
• License: http://purl.org/coar/access_right/c_14cb