基于距离最大熵值的蛋白质结构域边界检测系统

J4 ›› 2009, Vol. 47 ›› Issue (6): 1237-1240.

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Detection of Protein Domain Boundaries viaDistancebased Maximal Entropy

ZOU Shuxue, LIU Guixia, SHI Xiaohu, ZHOU Chunguang

College of Computer Science and Technology, Jilin University, Changchun 130012, China

Received:2009-02-23 Online:2009-11-26 Published:2010-01-07
Contact: ZHOU Chunguang E-mail:cgzhou@jlu.edu.cn.

Abstract

Abstract:

The domain detection was taken as an imbalanced data learning problem. A novel undersampling method using distancebased maximal entropy in the feature space of support vector machines is proposed. By way of scanning the selected proteins from the protein domain database, the overall accuracy of our machine study system is about 80% with high sensitivity and specificity.

Key words: protein domain boundaries, support vector machine, imbalanced data learning, distancebased maximal entropy

CLC Number:

ZOU Shuxue, LIU Guixia, SHI Xiaohu, ZHOU Chunguang. Detection of Protein Domain Boundaries viaDistancebased Maximal Entropy[J].J4, 2009, 47(6): 1237-1240.

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Detection of Protein Domain Boundaries viaDistancebased Maximal Entropy

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