Homology Detection Using Multilayer Maximum Clustering Coefficient

Journal of computational biology: A journal of computational molecular cell biology

CaioSantiago^1,2¹  VivianPereira^3²  LucianoDigiampietri^3³ 

[1] Address correspondence to: Caio Santiago, MS, Bioinformatics, University of São Paulo, Rua do Matão, 1010, São Paulo 05508-090, Brazil^1;Bioinformatics, University of São Paulo, São Paulo, Brazil^2;School of Arts, Sciences and Humanities, University of São Paulo, São Paulo, Brazil^3

关键词: clustering coefficient;    domain detection;    graph modeling;    homology detection;    local alignment;    sequence clustering;   

DOI  :  10.1089/cmb.2017.0266

学科分类：生物科学（综合）

来源: Mary Ann Liebert, Inc. Publishers

【 摘 要 】

Homologous sequences are widely used to understand the functions of certain genes or proteins. However, there is no consensus to solve the automatic assignment of functions to protein problem and many algorithms have different ways of identifying homologous clusters in a given set of sequences. In this article, we present an algorithm to deal with specific sets, the set of coding sequences obtained from phylogenetically close genomes (of the same species, genus, or family). When modeled as a graph, these sets have their own characteristics: they form more homogeneous and denser clusters. To solve this problem, our algorithm makes use of the clustering coefficient, which maximization can lead to the expected results from the biological point of view. In addition, we also present an algorithm for the identification of sequence domains based on graph topology. We also compared our results with those of the TribeMCL tool, a well-established algorithm of the area.

【 授权许可】

Unknown