The biological function of a protein is mainly maintained by its three-dimensional structure. Protein folds support the three-dimensional structure of a protein, and then the inter-residue contacts in the protein impact the formation of protein folds and the stability of its protein structure. Therefore, the protein contact plays a critical role in building protein structures and analyzing biological functions. In this thesis, we propose a methodology to predict the residue-residue contacts of a target protein and develop a new measurement to evaluate the accuracy of prediction. With three prediction tools, the support vector machine (SVM), the k-nearest neighbor algorithm (KNN), and the penalized discriminant analysis (PDA), we compare these classifiers based on the self-testing of the training set, which are derived from representative protein chains from PDB (PDB-REPRDB), and apply the best (SVM) to predict a testing set of 173 protein chains derived from previous study. The experimental results show that the accuracy of our prediction achieves 24.84%,15.68%, and 8.23% for three categories of different contacts, which greatly improves the result of random exploration (5.31%, 3.33%, and 1.12%, respectively).
Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0906111-150445 |
Date | 06 September 2011 |
Creators | Lin, Dong-Jian |
Contributors | Chung-Nan Lee, Yow-Ling Shiue, Kuo-Si Huang, Chang-Biau Yang |
Publisher | NSYSU |
Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0906111-150445 |
Rights | user_define, Copyright information available at source archive |
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