Weihuan Niu, Qingyou Xia and Guizhao Liang Pages 591 - 598 ( 8 )
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.
Factor analysis scales of generalized amino acid information (FASGAI), auto cross covariance (ACC), FASGAI-ACC, quantitative sequence-activity model (QSAM), support vector machines (SVM)
Key Laboratory of Biorheological Science and Technology (Chongqing University), Ministry of Education, Bioengineering college, Chongqing University, Chongqing 400044, China.