a network approach to predict pathogenic genes for fusarium graminearum一个网络的方法来预测花药对赤霉病致病基因.pdfVIP

A Network Approach to Predict Pathogenic Genes for Fusarium graminearum 1,2 3 1,3 1,4 Xiaoping Liu , Wei-Hua Tang , Xing-Ming Zhao *, Luonan Chen * 1 Institute of Systems Biology, Shanghai University, Shanghai, China, 2 School of Communication and Information Engineering, Shanghai University, Shanghai, China, 3 National Key Laboratory of Plant Molecular Genetics, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China, 4 Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China Abstract Fusarium graminearum is the pathogenic agent of Fusarium head blight (FHB), which is a destructive disease on wheat and barley, thereby causing huge economic loss and health problems to human by contaminating foods. Identifying pathogenic genes can shed light on pathogenesis underlying the interaction between F. graminearum and its plant host. However, it is difficult to detect pathogenic genes for this destructive pathogen by time-consuming and expensive molecular biological experiments in lab. On the other hand, computational methods provide an alternative way to solve this problem. Since pathogenesis is a complicated procedure that involves complex regulations and interactions, the molecular interaction network of F. graminearum can give clues to potential pathogenic genes. Furthermore, the gene expression data of F. graminearum before and after its invasion into plant host can also provide useful information. In this paper, a novel systems biology approach is presented to predict pathogenic genes of F. graminearum based on molecular interaction network and gene