Extraction of Protein Sequence Motif Information using PSO K-Means
This work addresses protein function analysis for bioinformatics researchers, but it is incremental as it applies an existing optimization method to a known clustering task.
The paper tackled the problem of extracting protein sequence motif information by using a PSO-optimized k-means algorithm, resulting in a comparison of motif information from clusters and biclusters based on protein structure homogeneity.
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.