title: Prediction of protein structure classes by incorporating different protein descriptors into general Chou's pseudo amino acid composition.
abstract: Successful protein structure identification enables researchers to estimate the biological functions of proteins, yet it remains a challenging problem. The most common method for determining an unknown protein's structural class is to perform expensive and time-consuming manual experiments. Because of the availability of amino acid sequences generated in the post-genomic age, it is possible to predict an unknown protein's structural class using machine learning methods given a protein's amino-acid sequence and/or its secondary structural elements. Following recent research in this area, we propose a new machine learning system that is based on combining several protein descriptors extracted from different protein representations, such as position specific scoring matrix (PSSM), the amino-acid sequence, and secondary structural sequences. The prediction engine of our system is operated by an ensemble of support vector machines (SVMs), where each SVM is trained on a different descriptor. The results of each SVM are combined by sum rule. Our final ensemble produces a success rate that is substantially better than previously reported results on three well-established datasets. The MATLAB code and datasets used in our experiments are freely available for future comparison at http://www.dei.unipd.it/node/2357.
authors.affiliation: DEI, University of Padua, Viale Gradenigo 6, Padua, Italy. Electronic address: loris.nanni@unipd.it.
authors.forename: Loris
authors.initials: L
authors.lastname: Nanni
authors.affiliation: Computer Information Systems, Missouri State University, 901 S. National, Springfield, MO 65804, USA. Electronic address: alessandra.lumini@unibo.it.
authors.forename: Sheryl
authors.initials: S
authors.lastname: Brahnam
authors.affiliation: DISI, Università di Bologna, Via Venezia 52, 47521 Cesena, Italy. Electronic address: sbrahnam@missouristate.edu.
authors.forename: Alessandra
authors.initials: A
authors.lastname: Lumini
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D001185:Artificial Intelligence; D008957:Models, Genetic; D011487:Protein Conformation; D011506:Proteins / Q000145:classification* / Q000235:genetics*; D012984:Software; D060388:Support Vector Machine
chemical_list: D011506:Proteins
keywords: Ensemble of classifiers; Machine learning; Protein descriptors; Protein structure class; Support vector machines