Incorporating Support Vector Machine for Identifying Protein Tyrosine Sulfation Sites

ASIA unversity > 資訊學院 > 生物資訊與醫學工程學系 > 期刊論文 > Item 310904400/8519

jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://asiair.asia.edu.tw/ir/handle/310904400/8519

题名:	Incorporating Support Vector Machine for Identifying Protein Tyrosine Sulfation Sites
作者:	Chang, WC (Chang, Wen-Chi);Lee, TY (Lee, Tzong-Yi);Shien, DM (Shien, Dray-Ming);Hsu, JBK (Hsu, Justin Bo-Kai);Horng, JT (Horng, Jorng-Tzong);Hsu, PC (Hsu, Po-Chiang);Wang, TY (Wang, Ting-Yuan);Huang, HD (Huang, Hsien-Da);Pan, RL (Pan, Rong-Long)
贡献者:	Department of Bioinformatics
关键词:	protein;sulfation;prediction
日期:	2009-11
上传时间:	2010-03-26 02:56:34 (UTC+0)
出版者:	Asia University
摘要:	Abstract: Tyrosine sulfation is a post-translational modification of many secreted and membrane-bound proteins. It governs protein-protein interactions that are involved in leukocyte adhesion, hemostasis, and chemokine signaling. However, the intrinsic feature of sulfated protein remains elusive and remains to be delineated. This investigation presents SulfoSite, which is a computational method based on a support vector machine (SVM) for predicting protein sulfotyrosine sites. The approach was developed to consider structural information such as concerning the secondary structure and solvent accessibility of amino acids that surround the sulfotyrosine sites. One hundred sixty-two experimentally verified tyrosine sulfation sites were identified using UniProtKB/SwissProt release 53.0. The results of a five-fold cross-validation evaluation suggest that the accessibility of the solvent around the sulfotyrosine sites contributes substantially to predictive accuracy. The SVM classifier can achieve an accuracy of 94.2% in fivefold cross validation when sequence positional weighted matrix (PWM) is coupled with values of the accessible surface area (ASA). The proposed method significantly outperforms previous methods for accurately predicting the location of tyrosine sulfation sites. (C) 2009 Wiley Periodicals, Inc. J Comput Chem 30: 2526-2537, 2009
關聯:	JOURNAL OF COMPUTATIONAL CHEMISTRY 30 (15): 2526-2537
显示于类别:	[生物資訊與醫學工程學系 ] 期刊論文

文件中的档案:

档案	描述	大小	格式	浏览次数
		0Kb	Unknown	570	检视/开启
23.doc		45Kb	Microsoft Word	479	检视/开启

在ASIAIR中所有的数据项都受到原著作权保护.

数据加载中.....