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A New Fitness Function for Evaluating the Quality of Predicted Protein Structures

For understanding the function of a protein, the protein structure plays an important role. The prediction of protein structure from its primary sequence has significant assistance in bioinformatics. Generally, the real protein structures can be reconstructed by some costly techniques, but predicting the protein structures helps us guess the functional expression of a protein in advance. In this thesis, we develop three terms as the materials of the fitness function that can be successfully used in protein backbone structure prediction. In the result of this thesis, it shows that over 80% of good values calculated from our fitness function, which are generated by the genetic programming, are better than the average in the CASP8.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0902110-103900
Date02 September 2010
CreatorsChen, Chun-jen
ContributorsKuo-Tsung Tseng, Chang-Biau Yang, Shih-Chung Chen, Chung-Lung Cho, Jyh-Jian Sheu
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0902110-103900
Rightsoff_campus_withheld, Copyright information available at source archive

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