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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Format: | Thesis |
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2010.
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Online Access: | Get fulltext |