title: LPC cepstral distortion measure for protein sequence comparison.
abstract: Protein sequence comparison is the most powerful tool for the inference of novel protein structure and function. This type of inference is commonly based on the similar sequence-similar structure-similar function paradigm, and derived by sequence similarity searching on databases of protein sequences. As entire genomes have been being determined at a rapid rate, computational methods for comparing protein sequences will be more essential for probing the complexity of molecular machines. In this paper we introduce a pattern-comparison algorithm, which is based on the mathematical concepts of linear predictive coding (LPC) and LPC cepstral distortion measure, for computing similarities/dissimilarities between protein sequences. Experimental results on a real data set of functionally related and functionally nonrelated protein sequences have shown the effectiveness of the proposed approach on both accuracy and computational efficiency.
authors.affiliation: Bioinformatics Applications Research Center, School of Information Technology, James Cook University, Townsville, QLD 4811, Australia. tuan.pham@jcu.edu.au
authors.forename: Tuan D
authors.initials: TD
authors.lastname: Pham
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D016014:Linear Models; D008956:Models, Chemical; D008958:Models, Molecular; D010363:Pattern Recognition, Automated / Q000379:methods*; D011506:Proteins / Q000737:chemistry* / Q000145:classification; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*
chemical_list: D011506:Proteins