Neural network for prediction of cysteine disulphide bridge connectivity in proteins

The goal of this thesis is to develop a computational method based on machine learning techniques for predicting disulfide-bonding states of Cysteine residues in proteins, which is a sub-problem of the bigger and yet unsolved problem of protein structure prediction. First, we preprocessed the datase...

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Bibliographic Details
Main Author: Bostan, Hamed
Format: Thesis
Language:English
Published: 2010
Subjects:
Online Access:http://eprints.utm.my/id/eprint/18275/1/HamedBostanMFSKSM2010.pdf
http://eprints.utm.my/id/eprint/18275/
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Institution: Universiti Teknologi Malaysia
Language: English