Title: MESSM: a framework for protein fold recognition using Neural Networks and Support Vector Machines

 

Author: Nan Jiang, Wendy Wu, Ian Mitchell

 

Addresses:
School of Computing Science, Middlesex University, London EN4 4BT, UK.
School of Computing Science, Middlesex University, London EN4 4BT, UK.
School of Computing Science, Middlesex University, London EN4 4BT, UK

 

Journal: Int. J. of Bioinformatics Research and Applications, 2006 Vol.2, No.4, pp.381 - 393

 

Abstract: A new framework (called MESSM) for protein fold recognition with three key features is proposed in this paper. Being tested on three benchmark problems, the results show that the MESSM has a comparable performance on fold recognition to those more computational intensive, energy potential based fold recognition models. The MESSM leads to a better performance on alignment accuracy. The MESSM presents a new way to develop an efficient tool for protein fold recognition.

 

Keywords: protein fold recognition; neural networks; NNs; support vector machines; SVMs; substitution matrix; energy potential; bioinformatics research; bioinformatics applications; high performance computing.

 

DOI: 10.1504/IJBRA.2006.011037

10.1504/06.11037

 

 

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