期刊论文、会议论文

Jiang, Xingpeng（蒋兴鹏）

英文

Lecture Notes in Computer Science

0302-9743

2018

10955

389-394

14th International Conference on Intelligent Computing (ICIC)

Lecture Notes in Computer Science

AUG 15-18, 2018

Wuhan, PEOPLES R CHINA

[Chen, Sisi;Liu, Dan;Zheng, Jia;Hu, Xiaohua;Jiang, Xingpeng] Cent China Normal Univ, Sch Comp, Wuhan 430079, Hubei, Peoples R China.^[Chen, Pingtao] Univ Sci & Technol China, Sch Phys Sci, Hefei 230026, Anhui, Peoples R China.^[Hu, Xiaohua] Drexel Univ, Coll Comp & Informat, Philadelphia, PA 19104 USA.

IEEE Computat Intelligence Soc, Int Neural Network Soc, Natl Sci Fdn China, Tongji Univ, Wuhan Univ Sci & Technol, Wuhan Inst Technol

Huang, DS Jo, KH Zhang, XL

GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND

SPRINGER INTERNATIONAL PUBLISHING AG

978-3-319-95932-0; 978-3-319-95933-7

10.1007/978-3-319-95933-7_47

National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61532008]; Excellent Doctoral Breeding Project of CCNU; Self-determined Research Funds of CCNU from the Colleges' Basic Research and Operation of MOE [CCNU16KFY04]

本校为第一且通讯机构

The study of microbe-disease associations can be utilized as a valuable material for understanding disease pathogenesis. Developing a highly accurate algorithm model for predicting disease-related microbes will provide a basis for targeted treatment of the disease. In this paper, we propose an approach based on Kernelized Bayesian Matrix Factorization (KBMF) to predict microbe-disease association, based on the Gaussian interaction profile kernel similarity for microbes and diseases. The prediction performance of the method was evaluated by five-fold cross validation. KBMF achieved reliable res...