Support vector machines for predicting the specificity of GaINAc-transferase

被引：66

作者：

Cai, YD

Liu, XJ

Xu, XB

Chou, KC

机构：

[1] Chinese Acad Sci, Shanghai Res Ctr Biotechnol, Shanghai 200233, Peoples R China

[2] Univ Edinburgh, Inst Cell Anim & Populat Biol, Edinburgh EH9 3JT, Midlothian, Scotland

[3] Univ Wales Coll Cardiff, Coll Cardiff, Dept Comp Sci, Cardiff CF2 3XF, S Glam, Wales

[4] Upjohn Co, Upjohn Labs, Comp Aided Drug Discovery, Kalamazoo, MI 49001 USA

来源：

PEPTIDES | 2002年 / 23卷 / 01期

关键词：

Support Vector Machines; GalNAc-transferase; self-consistency; jackknife test;

D O I：

10.1016/S0196-9781(01)00597-6

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

Support Vector Machines (SVMs) which is one kind of learning machines, was applied to predict the specificity of GalNAc-transferase. The examination for the self-consistency and the jackknife test of the SVMs method were tested for the training dataset (305 oligopeptides), the correct rate of self-consistency and jackknife test reaches 100%, and 84.9%, respectively. Furthermore, the prediction of the independent testing dataset (30 oligopeptides) was tested, the rate reaches 76.67%. (C) 2002 Elsevier Science Inc. All rights reserved.

引用

页码：205 / 208

页数：4

共 13 条

[1]

[Anonymous], 1999, INT C MACH LEARN ICM

[2]

[Anonymous], 1999, REPOSIT TU DORTMUND, DOI DOI 10.17877/DE290R-5098

[3]

BURBIDGE R, 2000, P AISB 00 S ART INT, P1

[4] Artificial neural network model for predicting the specificity of GalNAc-transferase [J].