Literature DB >> 30102565

Homology Detection Using Multilayer Maximum Clustering Coefficient.

Caio Santiago1, Vivian Pereira2, Luciano Digiampietri2.   

Abstract

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.

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

Year:  2018        PMID: 30102565     DOI: 10.1089/cmb.2017.0266

Source DB:  PubMed          Journal:  J Comput Biol        ISSN: 1066-5277            Impact factor:   1.479


  2 in total

1.  Graph-Directed Approach for Downselecting Toxins for Experimental Structure Determination.

Authors:  Rachael A Mansbach; Srirupa Chakraborty; Timothy Travers; S Gnanakaran
Journal:  Mar Drugs       Date:  2020-05-14       Impact factor: 5.118

2.  Gene Tags Assessment by Comparative Genomics (GTACG): A User-Friendly Framework for Bacterial Comparative Genomics.

Authors:  Caio Rafael do Nascimento Santiago; Renata de Almeida Barbosa Assis; Leandro Marcio Moreira; Luciano Antonio Digiampietri
Journal:  Front Genet       Date:  2019-08-26       Impact factor: 4.599

  2 in total

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