PredCSF: An Integrated Feature-Based Approach for Predicting Conotoxin Superfamily
文献类型：期刊论文
| 作者 | Fan, Yong-Xian1,2; Song, Jiangning3,4; Kong, Xiangzeng5; Shen, Hong-Bin1,2 |
| 刊名 | PROTEIN AND PEPTIDE LETTERS
 |
| 出版日期 | 2011 |
| 卷号 | 18期号:3页码:261-267 |
| 关键词 | Conotoxin physicochemical property wavelet analysis random forest PSSM PredCSF |
| 英文摘要 | Conotoxins are small disulfide-rich peptides that are invaluable channel-targeted peptides and target neuronal receptors. They show prospects for being potent pharmaceuticals in the treatment of Alzheimer's disease, Parkinson's disease, and epilepsy. Accurate and fast prediction of conotoxin superfamily is very helpful towards the understanding of its biological and pharmacological functions especially in the post-genomic era. In the present study, we have developed a novel approach called PredCSF for predicting the conotoxin superfamily from the amino acid sequence directly based on fusing different kinds of sequential features by using modified one-versus-rest SVMs. The input features to the PredCSF classifiers are composed of physicochemical properties, evolutionary information, predicted secondary structure and amino acid composition, where the most important features are further screened by random forest feature selection to improve the prediction performance. The results show that PredCSF can obtain an overall accuracy of 90.65% based on a benchmark dataset constructed from the most recent database, which consists of 4 main conotoxin superfamilies and 1 class of non-conotoxin class. Systematic experiments also show that combing different features is helpful for enhancing the prediction power when dealing with complex biological problems. PredCSF is expected to be a powerful tool for in silico identification of novel conotonxins and is freely available for academic use at http://www.csbio.sjtu.edu.cn/bioinf/PredCSF. |
| WOS标题词 | Science & Technology ; Life Sciences & Biomedicine |
| 类目[WOS] | Biochemistry & Molecular Biology |
| 研究领域[WOS] | Biochemistry & Molecular Biology |
| 关键词[WOS] | AMINO-ACID-COMPOSITION ; SECONDARY STRUCTURE ; FEATURE-SELECTION ; PROTEIN ; CONOPEPTIDES ; INFORMATION |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000288983800006 |
| 公开日期 | 2014-11-23 |
| 源URL | [http://124.16.173.210/handle/311007/414]  |
| 专题 | 天津工业生物技术研究所_结构生物信息学和整合系统生物学实验室 宋江宁_期刊论文 |
| 作者单位 | 1.Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China 2.Minist Educ China, Key Lab Syst Control & Informat Proc, Shanghai 200240, Peoples R China 3.Chinese Acad Sci, Tianjin Inst Ind Biotechnol, Tianjin 300308, Peoples R China 4.Monash Univ, Dept Biochem & Mol Biol, Melbourne, Vic 3800, Australia 5.Fujian Normal Univ, Sch Math & Comp Sci, Fuzhou 350007, Peoples R China |
| 推荐引用方式 GB/T 7714 | Fan, Yong-Xian,Song, Jiangning,Kong, Xiangzeng,et al. PredCSF: An Integrated Feature-Based Approach for Predicting Conotoxin Superfamily[J]. PROTEIN AND PEPTIDE LETTERS,2011,18(3):261-267. |
| APA | Fan, Yong-Xian,Song, Jiangning,Kong, Xiangzeng,&Shen, Hong-Bin.(2011).PredCSF: An Integrated Feature-Based Approach for Predicting Conotoxin Superfamily.PROTEIN AND PEPTIDE LETTERS,18(3),261-267. |
| MLA | Fan, Yong-Xian,et al."PredCSF: An Integrated Feature-Based Approach for Predicting Conotoxin Superfamily".PROTEIN AND PEPTIDE LETTERS 18.3(2011):261-267. |
入库方式： OAI收割
来源：天津工业生物技术研究所
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