Clique-finding Tool for Detecting Approximate Gene Clusters

Abstract

Defining relationships between species is a fundamental problem in bioinformatics. One of the ways to define relationships is to detect gene clusters. Graph concepts have been applied to several genomic studies. Approximate gene cluster discovery may be approached as optimization problems in graph, one of which is the Minimum Weight t-Partite Clique Problem (MWtCP). The goal of MWtCP is to create a t-partite graph and to find a t-star with minimum weight, which is used to approximate a t-clique. Clustar is a tool that applies an algorithm which solves the MWtCP for detecting gene clusters. It allows the user to detect gene clusters using three methods: approximate gene clustering, exact gene clustering (using GPU), and exact gene clustering (without using GPU). Clustar is able to produce candidate gene clusters and its alignment among the genomes, as well as the graph representation and the adjacency matrix produced from the generated graph.