sequencebasedproteinproteininteractionpredictionviasupportvectormachine

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	sequencebasedproteinproteininteractionpredictionviasupportvectormachine
	Wang Yongcui 1; Wang Jiguang 2; Yang Zhixia 3; Deng Naiyang 1
	2010
发表期刊	journalofsystemsscienceandcomplexity
ISSN	1009-6124
卷号	2010 期号:23 页码:1012－1023
摘要	This paper develops sequence-based methods for identifying novel protein-protein interactions (PPIs) by means of support vector machines (SVMs). The authors encode proteins ont only in the gene level but also in the amino acid level, and design a procedure to select negative training set for dealing with the training dataset imbalance problem, i.e., the number of interacting protein pairs is scarce relative to large scale non-interacting protein pairs. The proposed methods are validated on PPIs data of Plasmodium falciparum and Escherichia coli, and yields the predictive accuracy of 93.8% and 95.3%, respectively. The functional annotation analysis and database search indicate that our novel predictions are worthy of future experimental validation. The new methods will be useful supplementary tools for the future proteomics studies
语种	英语
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/37096
专题	中国科学院数学与系统科学研究院
作者单位	1.中国农业大学 2.中国科学院数学与系统科学研究院 3.新疆大学
推荐引用方式 GB/T 7714	Wang Yongcui,Wang Jiguang,Yang Zhixia,et al. sequencebasedproteinproteininteractionpredictionviasupportvectormachine[J]. journalofsystemsscienceandcomplexity,2010,2010(23):1012－1023.
APA	Wang Yongcui,Wang Jiguang,Yang Zhixia,&Deng Naiyang.(2010).sequencebasedproteinproteininteractionpredictionviasupportvectormachine.journalofsystemsscienceandcomplexity,2010(23),1012－1023.
MLA	Wang Yongcui,et al."sequencebasedproteinproteininteractionpredictionviasupportvectormachine".journalofsystemsscienceandcomplexity 2010.23(2010):1012－1023.