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	Inpreppi: an integrated evaluation method based on genomic context for predicting protein-protein interactions in prokaryotic genomes
	Sun, Jingchun1,2; Sun, Yan3,4; Ding, Guohui3,4; Liu, Qi5; Wang, Chuan3; He, Youyu3; Shi, Tieliu3; Li, Yixue3; Zhao, Zhongming1,2,6,7
刊名	Bmc bioinformatics
	2007-10-26
卷号	8页码:10
ISSN号	1471-2105
DOI	10.1186/1471-2105-8-414
通讯作者	Zhao, zhongming(zzhao@vcu.edu)
英文摘要	Background: although many genomic features have been used in the prediction of protein-protein interactions (ppis), frequently only one is used in a computational method. after realizing the limited power in the prediction using only one genomic feature, investigators are now moving toward integration. so far, there have been few integration studies for ppi prediction; one failed to yield appreciable improvement of prediction and the others did not conduct performance comparison. it remains unclear whether an integration of multiple genomic features can improve the ppi prediction and, if it can, how to integrate these features. results: in this study, we first performed a systematic evaluation on the ppi prediction in escherichia coli (e. coli) by four genomic context based methods: the phylogenetic profile method, the gene cluster method, the gene fusion method, and the gene neighbor method. the number of predicted ppis and the average degree in the predicted ppi networks varied greatly among the four methods. further, no method outperformed the others when we tested using three well-defined positive datasets from the kegg, ecocyc, and dip databases. based on these comparisons, we developed a novel integrated method, named inpreppi. inpreppi first normalizes the ac value (an integrated value of the accuracy and coverage) of each method using three positive datasets, then calculates a weight for each method, and finally uses the weight to calculate an integrated score for each protein pair predicted by the four genomic context based methods. we demonstrate that inpreppi outperforms each of the four individual methods and, in general, the other two existing integrated methods: the joint observation method and the integrated prediction method in string. these four methods and inpreppi are implemented in a user-friendly web interface. conclusion: this study evaluated the ppi prediction by four genomic context based methods, and presents an integrated evaluation method that shows better performance in e. coli.
WOS关键词	PHYLOGENETIC PROFILES ; FUNCTIONAL LINKAGES ; INTERACTION MAP ; NEIGHBORING GENES ; NETWORK ; ORGANISMS ; COEXPRESSION ; ORGANIZATION ; PROTEOMICS ; DATABASE
WOS研究方向	Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology
WOS类目	Biochemical Research Methods ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology
语种	英语
出版者	BIOMED CENTRAL LTD
WOS记录号	WOS:000252960300001
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/2380456
专题	中国科学院大学
通讯作者	Zhao, Zhongming
作者单位	1.Virginia Commonwealth Univ, Virginia Inst Psychiat & Behav Genet, Richmond, VA 23298 USA 2.Virginia Commonwealth Univ, Dept Psychiat, Richmond, VA 23298 USA 3.Chinese Acad Sci, Shanghai Inst Biol Sci, Bioinformat Ctr, Shanghai 200031, Peoples R China 4.Chinese Acad Sci, Grad Sch, Shanghai 200031, Peoples R China 5.Shanghai Jiao Tong Univ, Sch Life Sci & Technol, Shanghai 200240, Peoples R China 6.Virginia Commonwealth Univ, Dept Human Genet, Richmond, VA 23298 USA 7.Virginia Commonwealth Univ, Ctr Study Biol Complex, Richmond, VA 23284 USA
推荐引用方式 GB/T 7714	Sun, Jingchun,Sun, Yan,Ding, Guohui,et al. Inpreppi: an integrated evaluation method based on genomic context for predicting protein-protein interactions in prokaryotic genomes[J]. Bmc bioinformatics,2007,8:10.
APA	Sun, Jingchun.,Sun, Yan.,Ding, Guohui.,Liu, Qi.,Wang, Chuan.,...&Zhao, Zhongming.(2007).Inpreppi: an integrated evaluation method based on genomic context for predicting protein-protein interactions in prokaryotic genomes.Bmc bioinformatics,8,10.
MLA	Sun, Jingchun,et al."Inpreppi: an integrated evaluation method based on genomic context for predicting protein-protein interactions in prokaryotic genomes".Bmc bioinformatics 8(2007):10.

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