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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Main Author: | Bostan, Hamed |
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Format: | Thesis |
Language: | English |
Published: |
2010
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Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/18275/1/HamedBostanMFSKSM2010.pdf |
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