基于结构洞的多数据源融合关键蛋白质识别方法

doi:10.11896/jsjkx.200200004

计算机科学 ›› 2020, Vol. 47 ›› Issue (11A): 40-45.doi: 10.11896/jsjkx.200200004

基于结构洞的多数据源融合关键蛋白质识别方法

杨壮, 刘培强, 费兆杰, 刘畅

山东工商学院计算机科学与技术学院山东烟台 264005
山东省高等学校协同创新中心:未来智能计算山东烟台 264005

出版日期:2020-11-15 发布日期:2020-11-17
通讯作者: 刘培强(liupq@126.com)
作者简介:1083628707@qq.com
基金资助:
山东省自然科学基金(ZR2017MF049);烟台市重点研发计划项目(2017ZH065)

Essential Protein Identification Method Based on Structural Holes and Fusion of Multiple Data Sources

YANG Zhuang, LIU Pei-qiang, FEI Zhao-jie, LIU Chang

School of Computer Science and Technology,Shandong Technology and Business University,Yantai,Shandong 264005,China
Co-innovation Center of Shandong Colleges and Universities:Future Intelligent Computing,Yantai,Shandong 264005,China

Online:2020-11-15 Published:2020-11-17
About author:YANG Zhuang,born in 1992,MS.His main research interests include algorithms and complexity theory,and computational biology.
LIU Pei-qiang,born in 1970,Ph.D,professor,is a member of China Computer Federation.His main research interests include algorithms and complexity theory,and computational biology.
Supported by:
This work was supported by the Shandong Provincial Natural Science Foundation(ZR2017MF049) and Key Research and Development Program of Yantai City(2017ZH065).

摘要/Abstract

摘要： 关键蛋白质识别是当前计算生物学领域的一个研究热点和难点。通过计算方法识别关键蛋白质的方法主要有DC,BC,LAC,PeC,ION和LIDC等。现有方法的识别准确率还有待进一步提高,主要原因是其仅使用了蛋白质相互作用网络单一数据源,以及蛋白质相互作用网络中存在许多假阳性和假阴性数据等。为了提高识别准确率,提出一种高效识别方法PSHC。首先,PSHC方法首次把结构洞理论引入到关键蛋白质识别方法中;其次,融合了蛋白质相互作用网络和蛋白质复合物两种数据源用于识别关键蛋白质。在真实数据上的实验结果表明,与其他传统方法相比,PSHC方法可以识别更多关键蛋白质,并且敏感度、特异性、准确性、阳性预测值、阴性预测值、F测度等统计指标也明显高于其他方法。

关键词: 蛋白质复合物, 蛋白质相互作用网络, 关键蛋白质, 结构洞

Abstract: Essential protein identification is a hot research topic which is difficult in the field of computational biology.The exis-ting methods for identifying essential proteins by computational methods are mainly DC,BC,LAC,PeC,ION,and LIDC,yet the identification accuracy needs to be further improved,mainly because only one data source is used which is protein interaction network,and there are many false positive and false negative data in the network.In order to improve the identification accuracy,an efficient essential protein identification method PSHC is proposed.Firstly,the PSHC method introduced the structure hole theory into the essential protein identification method for the first time.Secondly,the PSHC method combines two data sources of protein interaction network and protein complex to identify the essential proteins.Experimental results on real data show that PSHC can identify more essential proteins than other traditional methods,and statistical indicators such as sensitivity,specificity,accuracy,positive predictive value,negative predictive value,and F-measure are also higher than other methods.

Key words: Essential proteins, Protein complex, Protein interaction network, Structural holes

中图分类号:

TP301

杨壮, 刘培强, 费兆杰, 刘畅. 基于结构洞的多数据源融合关键蛋白质识别方法[J]. 计算机科学, 2020, 47(11A): 40-45. https://doi.org/10.11896/jsjkx.200200004

YANG Zhuang, LIU Pei-qiang, FEI Zhao-jie, LIU Chang. Essential Protein Identification Method Based on Structural Holes and Fusion of Multiple Data Sources[J]. Computer Science, 2020, 47(11A): 40-45. https://doi.org/10.11896/jsjkx.200200004

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基于结构洞的多数据源融合关键蛋白质识别方法

Essential Protein Identification Method Based on Structural Holes and Fusion of Multiple Data Sources

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