Fuzzy k-nearest neighbor classifier to predict protein solvent accessibility

Jyh-Yeong Chang, Jia-Jie Shyu, Yi-Xiang Shi

研究成果同行評審

3 引文 斯高帕斯(Scopus)

摘要

The prediction of protein solvent accessibility is an intermediate step for predicting the tertiary structure of proteins. Knowledge of solvent accessibility has proved useful for identifying protein function, sequence motifs, and domains. Using a position-specific scoring matrix (PSSM) generated from PSI-BLAST in this paper, we develop the modified fuzzy k-nearest neighbor method to predict the protein relative solvent accessibility. By modifying the membership functions of the fuzzy k-nearest neighbor method by Sim et al. [1], has recently been applied to protein solvent accessibility prediction with excellent results. Our modified fuzzy k-nearest neighbor method is applied on the three-state, E, I, and B, and two-state, E, and B, relative solvent accessibility predictions, and its prediction accuracy compares favorly with those by the fuzzy k-NN and other approaches.
原文English
頁面837-845
頁數9
出版狀態Published - 11月 2007
事件14th International Conference on Neural Information Processing (ICONIP 2007) - Kitakyushu, 日本
持續時間: 13 11月 200716 11月 2007

Conference

Conference14th International Conference on Neural Information Processing (ICONIP 2007)
國家/地區日本
城市Kitakyushu
期間13/11/0716/11/07

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