Title :
Finding protein domain boundaries: an automated, non-homology-based method
Author :
Gurbaxani, Brian M. ; Mallick, Parag
Abstract :
A sequence-based methodology identifies the boundaries of structural domains in proteins. The method doesn\´t depend on knowledge of a protein\´s structure or on sequence homologs. We developed a Bayesian approach based on the statistical analysis of word content used in other fields. Our method first catalogs "pattern" frequencies - occurrences of groups of amino acids - in a nonredundant database of known protein domains and then uses the distributions of these patterns to identify regions of protein sequence that appear to signal the beginnings and ends of domains. The domain-delineating signals we\´ve produced using amino acid patterns show great promise in providing further insight into both the biochemistry and structural biology of proteins.
Keywords :
Bayes methods; biology computing; genetics; pattern recognition; proteins; statistical analysis; Bayesian approach; amino acids; automated nonhomology-based method; nonredundant database; pattern frequencies; protein domain boundaries; protein sequence; statistical analysis; Amino acids; Automatic generation control; Bioinformatics; Databases; Dictionaries; Diseases; Genomics; Humans; Protein sequence; Splicing; Bayesian algorithm; amino acid patterns; protein domains;
Journal_Title :
Intelligent Systems, IEEE
DOI :
10.1109/MIS.2005.106