Computational Identification of Protein-Protein Interactions in Rice Based on the Predicted Rice Interactome Network

作     者：Pengcheng Zhu Haibin Gu Yinming Jiao Donglin Huang Ming Chen 

作者机构：Department of Bioinformatics College of Life Sciences Zhejiang University Hangzhou 310058 China James D. Watson Institute of Genome Sciences Zhejiang University Hangzhou 310058 China State Key Laboratory of Plant Physiology and Biochemistry College of Life Sciences Zhejiang University Hangzhou 310058 China 

出 版 物：《Genomics, Proteomics & Bioinformatics》 (基因组蛋白质组与生物信息学报（英文版）)

年 卷 期：2011年第9卷第4期

页      面：128-137页

核心收录：

学科分类：0710[理学-生物学] 0831[工学-生物医学工程（可授工学、理学、医学学位）] 0711[理学-系统科学] 0832[工学-食品科学与工程（可授工学、农学学位）] 1001[医学-基础医学(可授医学、理学学位)] 07[理学] 08[工学] 0714[理学-统计学（可授理学、经济学学位）] 0703[理学-化学] 083202[工学-粮食、油脂及植物蛋白工程] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National Natural Science Foundation of China(Grant No.30771326,30971743,31050110121) the National Science and Technology Project of China(Grant No.2008AA10Z125,2008ZX08003-005,2009DFA32030) the Program for New Century Excellent Talents in University of China(Grant No.NCET-07-0740) 

主　　题：protein-protein interactions rice interactome interolog sub-network expansion pathway clustering 

摘      要：Plant protein-protein interaction networks have not been identified by large-scale experiments. In order to better understand the protein interactions in rice, the Predicted Rice Interactome Network （PRIN; http：//***/ prin/） presented 76,585 predicted interactions involving 5,049 rice proteins. After mapping genomic features of rice （GO annotation, subcellular localizationprediction, and gene expression）, we found that a well-annotated and biologically significant network is rich enough to capture many significant functional linkages within higher-order biological systems, such as pathways and biological processes. Furthermore, we took MADS-box do- main-containing proteins and circadian rhythm signaling pathways as examples to demonstrate that functional protein complexes and biological pathways could be effectively expanded in our predicted network. The expanded molecular network in PRIN has considerably improved the capability of these analyses to integrate existing knowledge and provide novel insights into the function and coordination of genes and gene networks.