title: Linear discrimination of transmembrane from non-transmembrane segments in proteins using higher-order crossings.
abstract: Identification of transmembrane segments in protein sequences is an important issue in the field of bioinformatics. In this study, a method is proposed for linear discrimination between transmembrane and non-transmembrane segments, combining chemical and statistical features of the proteins with higher-order crossings analysis for protein segment classification. The method was tested on human proteins extracted from public available databases and the results have shown a remarkable efficiency of the proposed algorithm to correctly classify the sequence segments under study into two linearly separated classes, for a wide range of transmembrane segment lengths.
authors.affiliation: Dept. of Electr. & Comput. Eng., Aristotle Univ. of Thessaloniki, Thessaloniki, Greece. ikitsas@auth.gr
authors.forename: Ilias K
authors.initials: IK
authors.lastname: Kitsas
authors.forename: Stavros M
authors.initials: SM
authors.lastname: Panas
authors.forename: Leontios J
authors.initials: LJ
authors.lastname: Hadjileontiadis
mesh_terms: D000465:Algorithms; D000596:Amino Acids / Q000737:chemistry; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D030562:Databases, Protein; D006801:Humans; D007700:Kinetics; D015233:Models, Statistical; D016011:Normal Distribution; D025941:Protein Interaction Mapping; D017433:Protein Structure, Secondary; D040901:Proteomics / Q000379:methods*; D015203:Reproducibility of Results; D016415:Sequence Alignment; D020539:Sequence Analysis, Protein
chemical_list: D000596:Amino Acids