Parallel Approach for Visual Clustering of Protein Databases

Abstract

Visualization of a large-scale protein databases may help biologists in discovering similarity between sequences of different organisms. In this article we present a complex approach for visually representing relations between proteins in large scale databases. Our approach includes sequence alignment, mutual distance measurement, clustering and classification of protein sequences. We propose a visual representation method for considered as well-established Pfam 4.0 proteins database. Our objective is to visually reflect the similarity of protein sequences in three dimensional space using non-standard approach.