標題: | Prediction of Non-classical Secreted Proteins Using Informative Physicochemical Properties |
作者: | Hung, Chiung-Hui Huang, Hui-Ling Hsu, Kai-Ti Ho, Shinn-Jang Ho, Shinn-Ying 生物科技學系 生物資訊及系統生物研究所 Department of Biological Science and Technology Institude of Bioinformatics and Systems Biology |
關鍵字: | amino acid index;non-classical secreted protein;SVM prediction |
公開日期: | 1-九月-2010 |
摘要: | The prediction of non-classical secreted proteins is a significant problem for drug discovery and development of disease diagnosis. The characteristic of non-classical secreted proteins is they are leaderless proteins without signal peptides in N-terminal. This characteristic makes the prediction of non-classical proteins more difficult and complicated than the classical secreted proteins. We identify a set of informative physicochemical properties of amino acid indices cooperated with support vector machine (SVM) to find discrimination between secreted and non-secreted proteins and to predict non-classical secreted proteins. When the sequence identity of dataset was reduced to 25%, the prediction accuracy on training dataset is 85% which is much better than the traditional sequence similarity-based BLAST or PSI-BLAST tool. The accuracy of independent test is 82%. The most effective features of prediction revealed the fundamental differences of physicochemical properties between secreted and non-secreted proteins. The interpretable and valuable information could be beneficial for drug discovery or the development of new blood biochemical examinations. |
URI: | http://dx.doi.org/10.1007/s12539-010-0023-z http://hdl.handle.net/11536/21951 |
ISSN: | 1913-2751 |
DOI: | 10.1007/s12539-010-0023-z |
期刊: | INTERDISCIPLINARY SCIENCES-COMPUTATIONAL LIFE SCIENCES |
Volume: | 2 |
Issue: | 3 |
起始頁: | 263 |
結束頁: | 270 |
顯示於類別: | 期刊論文 |