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  4. 结构生物信息学
Prediction and characterization of protein-protein interaction networks in swine

文献类型：期刊论文

作者Wang F1; Liu MX1; Song BX2; Li DY2; Pei HM3; Guo Y1; Huang JF[*]4; Zhang DL[*]2
刊名PROTEOME SCIENCE
出版日期2012
卷号10期号:x页码:2
关键词protein-protein interaction network Interolog D-MIST
通讯作者huangjf@mail.kiz.ac.cn ; zhangdeli@tsinghua.org.cn
合作状况其它
英文摘要Background: Studying the large-scale protein-protein interaction (PPI) network is important in understanding biological processes. The current research presents the first PPI map of swine, which aims to give new insights into understanding their biological processes.

Results: We used three methods, Interolog-based prediction of porcine PPI network, domain-motif interactions from structural topology-based prediction of porcine PPI network and motif-motif interactions from structural topology-based prediction of porcine PPI network, to predict porcine protein interactions among 25,767 porcine proteins. We predicted 20,213, 331,484, and 218,705 porcine PPIs respectively, merged the three results into 567,441 PPIs, constructed four PPI networks, and analyzed the topological properties of the porcine PPI networks. Our predictions were validated with Pfam domain annotations and GO annotations. Averages of 70, 10,495, and 863 interactions were related to the Pfam domain-interacting pairs in iPfam database. For comparison, randomized networks were generated, and averages of only 4.24, 66.79, and 44.26 interactions were associated with Pfam domain-interacting pairs in iPfam database. In GO annotations, we found 52.68%, 75.54%, 27.20% of the predicted PPIs sharing GO terms respectively. However, the number of PPI pairs sharing GO terms in the 10,000 randomized networks reached 52.68%, 75.54%, 27.20% is 0. Finally, we determined the accuracy and precision of the methods. The methods yielded accuracies of 0.92, 0.53, and 0.50 at precisions of about 0.93, 0.74, and 0.75, respectively.

Conclusion: The results reveal that the predicted PPI networks are considerably reliable. The present research is an important pioneering work on protein function research. The porcine PPI data set, the confidence score of each interaction and a list of related data are available at (http://pppid.biositemap.com/).
资助信息The present work was supported by Kunming Institute of Zoology, Chinese Academy of Sciences (Grant NO. Y002731071) and grants from the National Natural Science Foundations of China (Grant NO. 31072115).
收录类别SCI
语种英语
WOS记录号WOS:000301709000002
公开日期2012-04-20
源URL[http://159.226.149.42:8088/handle/152453/6924]  
专题昆明动物研究所_结构生物信息学
昆明动物研究所_遗传资源与进化国家重点实验室
作者单位1.College of Life Science, Center for Bioinformatics, Northwest A&F University, Yangling, Shaanxi 712100, China
2.College of Veterinary Medicine, Northwest A&F University, Yangling, Shaanxi 712100, China
3.College of forestry, Northwest A&F University, Yangling, Shaanxi 712100, China
4.State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, P.R. China
推荐引用方式
GB/T 7714		 Wang F,Liu MX,Song BX,et al. Prediction and characterization of protein-protein interaction networks in swine[J]. PROTEOME SCIENCE,2012,10(x):2.
APA Wang F.,Liu MX.,Song BX.,Li DY.,Pei HM.,...&Zhang DL[*].(2012).Prediction and characterization of protein-protein interaction networks in swine.PROTEOME SCIENCE,10(x),2.
MLA Wang F,et al."Prediction and characterization of protein-protein interaction networks in swine".PROTEOME SCIENCE 10.x(2012):2.

入库方式： OAI收割

来源：昆明动物研究所

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