Artif Intell Med 2017 05 24;78:41-46. Epub 2017 May 24.
College of Life Sciences, Zhejiang Sci-Tech University, Hangzhou 310018, China; School of Mathematics and Statistics, Hainan Normal University, Haikou 571158, China. Electronic address:
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J Theor Biol 2018 Jan 31;437:239-250. Epub 2017 Oct 31.
School of Mathematics and Statistics, Xidian University, Xi'an 710071, China.
Predicting protein subcellular location with support vector machine has been a popular research area recently because of the dramatic explosion of bioinformation. Though substantial achievements have been obtained, few researchers considered the problem of data imbalance before classification, which will lead to low accuracy for some categories. So in this work, we combined oversampling method with SVM to deal with the protein subcellular localization of unbalanced data sets. Read More
Math Biosci 2016 12 6;282:61-67. Epub 2016 Oct 6.
School of Mathematics and Statistics, Xidian University, Xi'an 710071, PR China.
Apoptosis, or programed cell death, plays a central role in the development and homeostasis of an organism. Obtaining information on subcellular location of apoptosis proteins is very helpful for understanding the apoptosis mechanism. The prediction of subcellular localization of an apoptosis protein is still a challenging task, and existing methods mainly based on protein primary sequences. Read More
J Theor Biol 2015 Feb 20;366:8-12. Epub 2014 Nov 20.
College of Information Technology, Shanghai Ocean University, Shanghai 201306, China. Electronic address:
Knowledge of apoptosis proteins plays an important role in understanding the mechanism of programmed cell death. Obtaining information on subcellular location of apoptosis proteins is very helpful to reveal the apoptosis mechanism and understand the function of apoptosis proteins. Because of the cost in time and labor associated with large-scale wet-bench experiments, computational prediction of apoptosis proteins subcellular location becomes very important and many computational tools have been developed in the recent decades. Read More
Int J Mol Sci 2012 17;13(2):2196-207. Epub 2012 Feb 17.
College of Computer Science and Information Technology, Northeast Normal University, 2555 Jingyue Street, Changchun 130117, China; E-Mail:
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. Read More