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A Multi-Scale Parameterization Approach of Peptides for Quantitative Sequence-Activity Models

[ Vol. 17 , Issue. 5 ]

Author(s):

Weihuan Niu, Qingyou Xia and Guizhao Liang   Pages 591 - 598 ( 8 )

Abstract:


A multi-scale parameterization approach, factor analysis scales of generalized amino acid information combined with auto cross covariance, was used to develop quantitative sequence-activity models of peptides using support vector machines. The results demonstrated that this approach could well characterize sequence features of the peptides studied.

Keywords:

Factor analysis scales of generalized amino acid information (FASGAI), auto cross covariance (ACC), FASGAI-ACC, quantitative sequence-activity model (QSAM), support vector machines (SVM)

Affiliation:

Key Laboratory of Biorheological Science and Technology (Chongqing University), Ministry of Education, Bioengineering college, Chongqing University, Chongqing 400044, China.



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