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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书目详细资料
主要作者: Bostan, Hamed
格式: Thesis
语言:英语
出版: 2010
主题:
在线阅读:http://eprints.utm.my/18275/1/HamedBostanMFSKSM2010.pdf