title: Using support vector machine and evolutionary profiles to predict antifreeze protein sequences.
abstract: Antifreeze proteins (AFPs) are ice-binding proteins. Accurate identification of new AFPs is important in understanding ice-protein interactions and creating novel ice-binding domains in other proteins. In this paper, an accurate method, called AFP_PSSM, has been developed for predicting antifreeze proteins using a support vector machine (SVM) and position specific scoring matrix (PSSM) profiles. This is the first study in which evolutionary information in the form of PSSM profiles has been successfully used for predicting antifreeze proteins. Tested by 10-fold cross validation and independent test, the accuracy of the proposed method reaches 82.67% for the training dataset and 93.01% for the testing dataset, respectively. These results indicate that our predictor is a useful tool for predicting antifreeze proteins. A web server (AFP_PSSM) that implements the proposed predictor is freely available.
authors.affiliation: College of Computer Science and Information Technology, Northeast Normal University, 2555 Jingyue Street, Changchun 130117, China.|Key Laboratory of Intelligent Information Processing of Jilin Universities, Northeast Normal University, Changchun 130117, China.|College of Life Science, Northeast Normal University, 5268 Renmin Street, Changchun 130024, China.
authors.forename: Xiaowei
authors.initials: X
authors.lastname: Zhao
authors.affiliation: College of Computer Science and Information Technology, Northeast Normal University, 2555 Jingyue Street, Changchun 130117, China.|Key Laboratory of Intelligent Information Processing of Jilin Universities, Northeast Normal University, Changchun 130117, China.|College of Life Science, Northeast Normal University, 5268 Renmin Street, Changchun 130024, China.
authors.forename: Zhiqiang
authors.initials: Z
authors.lastname: Ma
authors.affiliation: College of Computer Science and Information Technology, Northeast Normal University, 2555 Jingyue Street, Changchun 130117, China.|Key Laboratory of Intelligent Information Processing of Jilin Universities, Northeast Normal University, Changchun 130117, China.
authors.forename: Minghao
authors.initials: M
authors.lastname: Yin
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D000596:Amino Acids / Q000737:chemistry; D021301:Antifreeze Proteins / Q000737:chemistry / Q000235:genetics; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D019143:Evolution, Molecular; D060388:Support Vector Machine; D014584:User-Computer Interface
chemical_list: D000596:Amino Acids; D021301:Antifreeze Proteins