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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Détails bibliographiques
Auteur principal:	Bostan, Hamed
Format:	Thèse
Langue:	anglais
Publié:	2010
Sujets:	QA75 Electronic computers. Computer science
Accès en ligne:	http://eprints.utm.my/18275/1/HamedBostanMFSKSM2010.pdf

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