Neural network for prediction of cysteine disulphide bridge connectivity in proteins

• Main Author: Bostan, Hamed
• Format: Thesis
• Language: English
• Published: 2010
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/18275/1/HamedBostanMFSKSM2010.pdf; http://eprints.utm.my/id/eprint/18275/
• Institution: Universiti Teknologi Malaysia

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...