Machine learning methods for prediction of disulphide bonding states of cysteine residues in proteins
The goal of this thesis work 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 a bigger and yet unsolved problem of protein structure prediction. Improvement in the prediction...
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| Format: | Doctoral Thesis |
| Language: | en |
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Alma Mater Studiorum - Università di Bologna
2010
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| Online Access: | http://amsdottorato.unibo.it/2588/ |