FMSClusterFinder: A new tool for detection and identification of clusters of sequential motifs with varying characteristics inside genomic sequences

Abstract

AbstractThis paper describes FMSClusterFinder, a new tool and algorithm for identification and detection of clusters of sequential blocks inside the DNA and RNA subject sequences. Gene expression and genomic groups’ performance is under the control of functional elements cooperating with each other as clusters. The functional motifs or blocks are often comparably short, degenerate and are located within varying distances from each other. Since functional motifs mostly act in relation to each other as clusters, finding such clusters of blocks is an effective approach to identify functional groups and their function and structure, which represents the need for development of new corresponding tools.The presented web application finds clusters of sequential blocks, with even altering sequences and located in varying distances from each other inside the subject sequences, simultaneously. Additionally, the blocks could be searched with user defined constant or varying characteristics such as: a) different levels of similarity, b) varying minimum number of blocks required to build up the query cluster, c) different types of sequence (degenerate or standard) and d) one or multiple alternative sequences for each block. FMSClusterFinder is available freely at http://fmsclusterfinder.fmsbiog.com.