Extraction of Protein Sequence Motif Information using PSO K-Means

TL;DR

This paper introduces an optimized PSO k-means clustering method to extract protein sequence motifs, comparing cluster and bicluster results to improve understanding of protein functionalities.

Contribution

The paper presents a novel application of PSO k-means for protein motif extraction and compares its effectiveness with biclustering techniques.

Findings

PSO k-means effectively extracts protein motifs based on sequence homogeneity.

Comparison shows differences between cluster and bicluster motif information.

Optimized clustering improves protein function analysis.

Abstract

The main objective of the paper is to find the motif information.The functionalities of the proteins are ideally found from their motif information which is extracted using various techniques like clustering with k-means, hybrid k-means, self-organising maps, etc., in the literature. In this work protein sequence information is extracted using optimised k-means algorithm. The particle swarm optimisation technique is one of the frequently used optimisation method. In the current work the PSO k-means is used for motif information extraction. This paper also deals with the comparison between the motif information obtained from clusters and biclustersusing PSO k-means algorithm. The motif information acquired is based on the structure homogeneity of the protein sequence.