Prediction of subcelluar localization using maximal-margin spherical support vector machine

Wei Ming Chen, I. Lin Wu, Jung-Hsien Chiang, Pei Yi Hao

研究成果: Conference contribution

摘要

Prediction of subcellular localization of various proteins is an important and well-studied problem. Each compartment in cell has specific tasks, and proteins in each compartment are synthesized to fulfill these tasks, and for this reason, an effective predictive system for protein subcellular localization is crucial. Therefore, we propose a prediction based on maximal margin sphere-structure multi-class support vector, and use some different types of composition in amino acid for features. The experimental results show that the proposed method is better than transitional support vector machine.

原文English
主出版物標題2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010
頁面1476-1481
頁數6
DOIs
出版狀態Published - 2010 十一月 15
事件2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010 - Qingdao, China
持續時間: 2010 七月 112010 七月 14

出版系列

名字2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010
3

Other

Other2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010
國家China
城市Qingdao
期間10-07-1110-07-14

    指紋

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Human-Computer Interaction

引用此

Chen, W. M., Wu, I. L., Chiang, J-H., & Hao, P. Y. (2010). Prediction of subcelluar localization using maximal-margin spherical support vector machine. 於 2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010 (頁 1476-1481). [5580840] (2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010; 卷 3). https://doi.org/10.1109/ICMLC.2010.5580840