Sequence-based protein-protein interaction prediction via support vector machine
文献类型：期刊论文
| 作者 | Wang, Yongcui1,2; Wang, Jiguang3; Yang, Zhixia4; Deng, Naiyang1 |
| 刊名 | journal of systems science & complexity
 |
| 出版日期 | 2010-10-01 |
| 卷号 | 23期号:5页码:1012-1023 |
| 关键词 | Imbalance problem protein-protein interactions sequence-based support vector machine |
| ISSN号 | 1009-6124 |
| 中文摘要 | 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. |
| 英文摘要 | 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. |
| WOS标题词 | science & technology ; physical sciences |
| 类目[WOS] | mathematics, interdisciplinary applications |
| 研究领域[WOS] | mathematics |
| 关键词[WOS] | amino-acid-composition ; interaction network ; escherichia-coli ; database ; complexes ; resource ; update |
| 收录类别 | SCI ; ISTP |
| 语种 | 英语 |
| WOS记录号 | WOS:000284074000014 |
| 公开日期 | 2011-12-13 |
| 源URL | [http://ir.nwipb.ac.cn//handle/363003/1650]  |
| 专题 | 西北高原生物研究所_中国科学院西北高原生物研究所 |
| 作者单位 | 1.China Agr Univ, Coll Sci, Beijing 100083, Peoples R China 2.Chinese Acad Sci, NW Inst Plateau Biol, Key Lab Adaptat & Evolut Plateau Biota, Xining 810008, Peoples R China 3.Chinese Acad Sci, Acad Math & Syst Sci, Inst Syst Sci, Beijing 100190, Peoples R China 4.Xinjiang Univ, Coll Math & Syst Sci, Urumuchi 830046, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Yongcui,Wang, Jiguang,Yang, Zhixia,et al. Sequence-based protein-protein interaction prediction via support vector machine[J]. journal of systems science & complexity,2010,23(5):1012-1023. |
| APA | Wang, Yongcui,Wang, Jiguang,Yang, Zhixia,&Deng, Naiyang.(2010).Sequence-based protein-protein interaction prediction via support vector machine.journal of systems science & complexity,23(5),1012-1023. |
| MLA | Wang, Yongcui,et al."Sequence-based protein-protein interaction prediction via support vector machine".journal of systems science & complexity 23.5(2010):1012-1023. |
入库方式： OAI收割
来源：西北高原生物研究所
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