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...
Saved in:
Main Author: | |
---|---|
Format: | Thesis |
Language: | English |
Published: |
2010
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/18275/1/HamedBostanMFSKSM2010.pdf http://eprints.utm.my/id/eprint/18275/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Universiti Teknologi Malaysia |
Language: | English |