MESSM: a framework for protein fold recognition using neural networks and support vector machines.

Article

Mitchell, I., Jiang, N. and Wu, W. 2006. MESSM: a framework for protein fold recognition using neural networks and support vector machines. International Journal of Bioinformatics Research and Applications. 2 (4), pp. 381-393. https://doi.org/10.1504/IJBRA.2006.011037
TypeArticle
TitleMESSM: a framework for protein fold recognition using neural networks and support vector machines.
AuthorsMitchell, I., Jiang, N. and Wu, W.
Abstract

This paper presents the results of a PhD project that developed a framework, known as MESSM, for protein fold recognition. The framework has 3 key features: i) an environment-specific amino acid substitution is generated, ii) a mixed substitution mapping is performed by linearly combining the structurally derived substitution mapping with a sequence profile from well-developed amino acid substitution matrices, iii) Support Vector Machines are employed to measure the significance of the sequence-structure alignment. Tested on benchmark problems, MESSM was shown to lead to a better performance of alignment accuracy.

Research GroupArtificial Intelligence group
PublisherInderscience Publishers Limited
JournalInternational Journal of Bioinformatics Research and Applications
ISSN1744-5493
Publication dates
PrintOct 2006
Publication process dates
Deposited17 Oct 2008
Output statusPublished
Digital Object Identifier (DOI)https://doi.org/10.1504/IJBRA.2006.011037
LanguageEnglish
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