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题名: Sequence Based Prediction of Protein Mutant Stability and Discrimination of Thermophilic Proteins
作者: Gromiha, M. Michael;Huang, Liang-Tsung;Lai, Lien-Fu
贡献者: 資訊工程學系
关键词: Protein stability;Rule generator;Discrimination;Prediction;Thermophilic proteins;Neural network;Machine learning techniques
日期: 2008-10
上传时间: 2012-07-02T02:25:47Z
出版者: Springer
摘要: Prediction of protein stability upon amino acid substitution and discrimination of thermophilic proteins from mesophilic ones are important problems in designing stable proteins. We have developed a classification rule generator using the information about wild-type, mutant, three neighboring residues and experimentally observed stability data. Utilizing the rules, we have developed a method based on decision tree for discriminating the stabilizing and destabilizing mutants and predicting protein stability changes upon single point mutations, which showed an accuracy of 82% and a correlation of 0.70, respectively. In addition, we have systematically analyzed the characteristic features of amino acid residues in 3075 mesophilic and 1609 thermophilic proteins belonging to 9 and 15 families, respectively, and developed methods for discriminating them. The method based on neural network could discrimi-nate them at the 5-fold cross-validation accuracy of 89% in a dataset of 4684 proteins and 91% in a test set of 707 proteins.
關聯: The 3th International Conference on Pattern Recognition in Bioinformatics (PRIB 2008), Oct. 15-17, 2008: 15-17
显示于类别:[資訊工程學系] 會議論文


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