Protein Subcellular Localization Prediction for Fusarium graminearum

摘要：

The fungal pathogen Fusarium graminearum (telomorph Gibberella zeae) is the causal agent of several destructive crop diseases. Investigating subcellular tocalizations of E graminearum proteins can provide insight into pathogenic mechanisms underlying E graminearum-host interactions. In this paper, we design a novel balanced ensemble classifier based on support vector machines (SVMs) to predict F graminearum proteins subcellular localization from the primary sequence. The method is performed with a fungi dataset collected from UniProtKB database. In addition, we utilize SCL-BLAST (SubCellular Localization BLAST) to transfer annotations of homologous proteins to the target uncharacterized protein. We make three fold contributions to this filed. First, we present a new algorithm to cope with imbalance problem that arises in protein subcellular localization prediction, which can improve prediction accuracy significantly. Second, we employ feature selection techniques to find out most informative features for each compartment, and reduce computation cost and improve prediction accuracy at the same time. Third, we use BLAST to complement SVMs based methods, which makes our prediction more effective.

关键词： Fusarium graminearum protein subceilular localization re-balanced classifier

作者: Chenglei Sun Wei-Hua Tang Luonan Chen Xing-Ming Zhao

作者单位: Department of Mathematics,Shanghai University,China,200444 Institute of Systems Biology,Shanghai Uni Institute of Plant Physiology and Ecology,Shanghai Institutes for Biological Sciences,Chinese Academ Institute of Systems Biology,Shanghai University,China,200444 Department of Electrical Engineering a Institute of Systems Biology,Shanghai University,China,200444 Institute of Plant Physiology and Ecol

会议类型: 国际会议

会议名称: The 3rd International Symposium on Optimization and System Biology(第三届最优化与系统生物学国际会议 OSB09)

会议地点: 张家界

会议语种:英文

页码: 254-260

在线出版日期: 2009-09-20（万方平台首次上网日期，不代表论文的发表时间）