A Comparative Study on Sequence Feature Extraction for Type III Secreted Effector Prediction

摘要：

Protein secretion is an essential mechanism for bacterial survival in their surrounding environment The type III secretion system (T3SS) is a specialized protein delivery system that plays a key role in pathogens. Since the secretion mechanism has not been fully understood yet, T3SS has attracted a great deal of research interests. Especially, the identification of novel effectors (secreted proteins) is an important and challenging task for the T3SS study. This paper adopts machine learning methods to predict type III secreted effectors (T3SE). We conduct a comparative study on the feature extraction methods for protein sequence of T3SEs, and propose new methods involving sequence features, secondary structure and solvent accessibility information. The experimental results on Pseudomonas syringae data set demonstrate the effectiveness of our methods.

作者: Yang Yang

作者单位: Department of Computer Science and Engineering, Information Engineering College,Shanghai Maritime University, 1550 Haigang Ave., Shanghai 201306, China

会议类型: 国际会议

会议名称: 2011 Eighth International Conference on Fuzzy System and Knowledge Discovery(第八届模糊系统与知识发现国际会议 FSKD 2011)

会议地点: 上海

会议语种:英文

页码: 1608-1612

在线出版日期: 2011-07-26（万方平台首次上网日期，不代表论文的发表时间）