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A novel approach based on KATZ measure to predict associations of human microbiota with non-infectious diseases
Chen, X (Chen, Xing); Huang, YA (Huang, Yu-An); You, ZH (You, Zhu-Hong); Yan, GY (Yan, Gui-Ying); Wang, XS (Wang, Xue-Song)
2017
发表期刊BIOINFORMATICS
卷号33期号:5页码:733-739
摘要Motivation: Accumulating clinical observations have indicated that microbes living in the human body are closely associated with a wide range of human noninfectious diseases, which provides promising insights into the complex disease mechanism understanding. Predicting microbe-disease associations could not only boost human disease diagnostic and prognostic, but also improve the new drug development. However, little efforts have been attempted to understand and predict human microbe-disease associations on a large scale until now. Results: In this work, we constructed a microbe-human disease association network and further developed a novel computational model of KATZ measure for Human Microbe-Disease Association prediction (KATZHMDA) based on the assumption that functionally similar microbes tend to have similar interaction and non-interaction patterns with noninfectious diseases, and vice versa. To our knowledge, KATZHMDA is the first tool for microbe-disease association prediction. The reliable prediction performance could be attributed to the use of KATZ measurement, and the introduction of Gaussian interaction profile kernel similarity for microbes and diseases. LOOCV and k-fold cross validation were implemented to evaluate the effectiveness of this novel computational model based on known microbe-disease associations obtained from HMDAD database. As a result, KATZHMDA achieved reliable performance with average AUCs of 0.8130 +/- 0.0054, 0.8301 +/- 0.0033 and 0.8382 in 2-fold and 5-fold cross validation and LOOCV framework, respectively. It is anticipated that KATZHMDA could be used to obtain more novel microbes associated with important noninfectious human diseases and therefore benefit drug discovery and human medical improvement.
DOI10.1093/bioinformatics/btw715
WOS记录号WOS:000397265300014
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被引频次:24[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.xjipc.cas.cn/handle/365002/4789
专题多语种信息技术研究室
作者单位1.China Univ Min & Technol, Sch Informat & Elect Engn, Xuzhou 221116, Peoples R China
2.Hong Kong Polytechn Univ, Dept Comp, Hong Kong, Hong Kong, Peoples R China
3.Chinese Acad Sci, Xinjiang Tech Inst Phys & Chem, Urumqi 830011, Peoples R China
4.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
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Chen, X ,Huang, YA ,You, ZH ,et al. A novel approach based on KATZ measure to predict associations of human microbiota with non-infectious diseases[J]. BIOINFORMATICS,2017,33(5):733-739.
APA Chen, X ,Huang, YA ,You, ZH ,Yan, GY ,&Wang, XS .(2017).A novel approach based on KATZ measure to predict associations of human microbiota with non-infectious diseases.BIOINFORMATICS,33(5),733-739.
MLA Chen, X ,et al."A novel approach based on KATZ measure to predict associations of human microbiota with non-infectious diseases".BIOINFORMATICS 33.5(2017):733-739.
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