A novel approach based on KATZ measure to predict associations of human microbiota with non-infectious diseases
文献类型：期刊论文
| 作者 | Chen, Xing1; Huang, Yu-An2; You, Zhu-Hong3; Yan, Gui-Ying4 ; Wang, Xue-Song1
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| 刊名 | BIOINFORMATICS
 |
| 出版日期 | 2017-03-01 |
| 卷号 | 33期号:5页码:733-739 |
| ISSN号 | 1367-4803 |
| DOI | 10.1093/bioinformatics/btw715 |
| 英文摘要 | 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. |
| 资助项目 | National Natural Science Foundation of China[11301517] ; National Natural Science Foundation of China[11631014] ; National Natural Science Foundation of China[61572506] ; National Natural Science Foundation of China[11371355] ; Fundamental Research Funds for the Central Universities[2014YC07] |
| WOS研究方向 | Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Computer Science ; Mathematical & Computational Biology ; Mathematics |
| 语种 | 英语 |
| WOS记录号 | WOS:000397265300014 |
| 出版者 | OXFORD UNIV PRESS |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/24948]  |
| 专题 | 应用数学研究所 |
| 通讯作者 | Chen, Xing; You, Zhu-Hong; Wang, Xue-Song |
| 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 |
| 推荐引用方式 GB/T 7714 | Chen, Xing,Huang, Yu-An,You, Zhu-Hong,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, Xing,Huang, Yu-An,You, Zhu-Hong,Yan, Gui-Ying,&Wang, Xue-Song.(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, Xing,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. |
入库方式： OAI收割
来源：数学与系统科学研究院
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