期刊论文、会议论文

Hu, XH

英文

PROCEEDINGS 2018 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM)

2156-1125

2018

197-200

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

IEEE International Conference on Bioinformatics and Biomedicine-BIBM

DEC 03-06, 2018

Madrid, SPAIN

[Ma, Yingjun] Cent China Normal Univ, Sch Math & Stat, Wuhan, Hubei, Peoples R China.^[Ge, Leixin] Cent China Normal Univ, Sch Life Sci, Wuhan, Hubei, Peoples R China.^[Ma, Yuanyuan] Anyang Normal Univ, Sch Comp & Informat Engn, Anyang, Peoples R China.^[Jiang, Xingpeng;He, Tingting;Hu, Xiaohua] Cent China Normal Univ, Sch Comp, Wuhan, Hubei, Peoples R China.

Ulster Univ, Univ Granada, Univ Carlos III Madrid, TCCLS, IEEE, IEEE Comp Soc, Natl Sci Fdn, Syst Med, Mary Ann Liebert Inc publishers

Zheng, H Callejas, Z Griol, D Wang, H Hu, X Schmidt, H Baumbach, J Dickerson, J Zhang, L

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

978-1-5386-5488-0

10.1109/BIBM.2018.8621122

National Natural Science Foundation of China [61532008, 61872157]; National Key Research and Development Program of China [2017YFC0909502]

本校为第一且通讯机构

Studies have shown that microRNAs are functionally related to human diseases. However, experimental methods for detecting miRNA-disease associations are both time consuming and laborious. Therefore, a large number of computational models for predicting potential miRNA-disease interaction have been proposed. However, few methods take into account the nonlinear structural similarity of miRNAs (diseases) and effectively integrate multiple similar metrics into one network. In this paper, we propose a kernel-based soft-neighborhood network propagation algorithm (LKSNF) to predict potential miRNA-di...