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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| フォーマット: | 学位論文 |
| 言語: | 英語 |
| 出版事項: |
2010
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| 主題: | |
| オンライン･アクセス: | http://eprints.utm.my/18275/1/HamedBostanMFSKSM2010.pdf |