First report of knowledge discovery in predicting protein folding rate change upon single mutation

Lien Fu Lai, Chao Chin Wu, Liang Tsung Huang

研究成果: Conference contribution

1 引文 斯高帕斯(Scopus)

摘要

To explore the mechanism of protein folding is one of the important topics in protein research. The accurate prediction of protein folding rate change is helpful and useful in protein design. In earlier study, we have firstly analyzed the prediction of folding rate change upon single point mutation and constructed a non-redundant dataset of F467. F467 consists of 467 mutants with various features and widely distributed on secondary structure, solvent accessibility, conservation score and long-range contacts. In this work, we therefore focused on effectively developing the knowledge in F467 dataset. We have systematically analyzed the dataset and presented several representative data mining techniques, including decision tree, decision table and association rule algorithms. Furthermore, we have interpreted, evaluated, and compared the knowledge obtained from different techniques. The experimental results showed that the present approach can effectively develop the knowledge in the dataset and the outcomes can increase the understanding of predicting protein folding rate change upon single mutation. We have also created a website with related information about this work and it is freely available at http://bioinformatics. myweb.hinet.net/kdfreedom.htm .

原文English
主出版物標題Bio-Inspired Computing and Applications - 7th International Conference on Intelligent Computing, ICIC 2011, Revised Selected Papers
頁面624-631
頁數8
DOIs
出版狀態Published - 2011 十二月 1
事件7th International Conference on Intelligent Computing, ICIC 2011 - Zhengzhou, China
持續時間: 2011 八月 112011 八月 14

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
6840 LNBI
ISSN(列印)0302-9743
ISSN(電子)1611-3349

Other

Other7th International Conference on Intelligent Computing, ICIC 2011
國家China
城市Zhengzhou
期間11-08-1111-08-14

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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