Automatic 2D hydrophobic cluster alignment

Abstract

Biological databases in the past decade have tremendously grown in size. However, effective retrieval data is still a great challenge. In particular, we need a high-quality tool to measure similarity among protein sequences within the database instead of 1D alignment software. In this work, we implement a 2D visualisation tool for amino acid and propose a new protein representation that could be used effectively in our 2D automatic Hydrophobic Cluster Alignment software. The resulting evolution trees and the alignment results from the PIR database have demonstrated that homologous proteins with the same functionalities obtain high sequence identity score.