Provides an efficient computational model that offers deep representations-based miRNA–disease association prediction. DRMDA is an algorithm that calculates the score of each miRNA–disease sample by analysing known miRNA–disease interactions, disease semantic similarity and miRNA functional similarity. Then, potential associations were selected according to the score. It finds out deep representation under the surface of disease semantic similarity.
School of Information and Control Engineering, China; University of Mining and Technology, Xuzhou, China; School of Life Science, Peking University, Beijing, China; Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Science, Urumqi, China; School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, China
DRMDA funding source(s)
Supported by National Natural Science Foundation of China under Grant No. 11631014 and No. 61572506 and by Pioneer Hundred Talents Program of Chinese Academy of Sciences.