XJIPC OpenIR  > 多语种信息技术研究室
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
ISSN1367-4803
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
引用统计
被引频次:28[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
推荐引用方式
GB/T 7714
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.
条目包含的文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
A novel approach bas(316KB)期刊论文作者接受稿开放获取CC BY-NC-SA浏览 请求全文
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Chen, X (Chen, Xing)]的文章
[Huang, YA (Huang, Yu-An)]的文章
[You, ZH (You, Zhu-Hong)]的文章
百度学术
百度学术中相似的文章
[Chen, X (Chen, Xing)]的文章
[Huang, YA (Huang, Yu-An)]的文章
[You, ZH (You, Zhu-Hong)]的文章
必应学术
必应学术中相似的文章
[Chen, X (Chen, Xing)]的文章
[Huang, YA (Huang, Yu-An)]的文章
[You, ZH (You, Zhu-Hong)]的文章
相关权益政策
暂无数据
收藏/分享
文件名: A novel approach based on KATZ measure to predict associations of human microbiota with non-infectious diseases.pdf
格式: Adobe PDF
此文件暂不支持浏览
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。