On using physico-chemical properties of amino acids in string kernels for protein classification via support vector machines

2015 ◽  
Vol 28 (2) ◽  
pp. 504-516
Author(s):  
Limin Li ◽  
Kiyoko F. Aoki-Kinoshita ◽  
Wai-Ki Ching ◽  
Hao Jiang
Keyword(s):  
Amino Acids ◽  
Support Vector Machines ◽  
Chemical Properties ◽  
Support Vector ◽  
Protein Classification ◽  
String Kernels ◽  
Physico Chemical ◽  
Vector Machines

scholarly journals Conotoxin protein classification using free scores of words and support vector machines

2011 ◽  
Vol 12 (1) ◽  
Author(s):  
Nazar Zaki ◽  
Stefan Wolfsheimer ◽  
Gregory Nuel ◽  
Sawsan Khuri
Keyword(s):  
Support Vector Machines ◽  
Support Vector ◽  
Protein Classification ◽  
Vector Machines

PredHydroxy: computational prediction of protein hydroxylation site locations based on the primary structure

2015 ◽  
Vol 11 (3) ◽  
pp. 819-825 ◽  
Author(s):  
Shao-Ping Shi ◽  
Xiang Chen ◽  
Hao-Dong Xu ◽  
Jian-Ding Qiu
Keyword(s):  
Amino Acids ◽  
Support Vector Machines ◽  
Primary Structure ◽  
Computational Prediction ◽  
Support Vector ◽  
Quality Indices ◽  
High Quality ◽  
Vector Machines ◽  
Amino Acids Composition

A predictor PredHydroxy, based on position weight amino acids composition, 8 high-quality indices and support vector machines, is designed to identify hydroxyproline and hydroxylysine sites.

scholarly journals POPISK: T-cell reactivity prediction using support vector machines and string kernels

2011 ◽  
Vol 12 (1) ◽  
pp. 446 ◽  
Author(s):  
Chun-Wei Tung ◽  
Matthias Ziehm ◽  
Andreas Kämper ◽  
Oliver Kohlbacher ◽  
Shinn-Ying Ho
Keyword(s):  
T Cell ◽  
Support Vector Machines ◽  
Support Vector ◽  
Cell Reactivity ◽  
String Kernels ◽  
Vector Machines ◽  
T Cell Reactivity
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