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

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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.

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

Document Type: Research Article

Publication date: 01 May 2010

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  • Protein & Peptide Letters publishes short papers in all important aspects of protein and peptide research, including structural studies, recombinant expression, function, synthesis, enzymology, immunology, molecular modeling, drug design etc. Manuscripts must have a significant element of novelty, timeliness and urgency that merit rapid publication. Reports of crystallisation, and preliminary structure determinations of biologically important proteins are acceptable. Purely theoretical papers are also acceptable provided they provide new insight into the principles of protein/peptide structure and function.
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