College of Information and Electronic Engineering, Hunan City University, Yiyang 413000, China<&wdkj&>College of Computer Science and Electronic Engineering, Key Laboratory for Embedded and Cyber-Physical Systems, Hunan University, Changsha 410082, China<&wdkj&>College of Computer Science and Electronic Engineering, Key Laboratory for Embedded and Cyber-Physical Systems, Hunan University, Changsha 410082, China
This work was supported in part by the National Natural Science Foundation of China under Grant 61873089 , 62032007 and the Key Project of the Education Department of Hunan Province under Grant 20A087 , the Innovation Platform Open Fund Project of Hunan Provincial Education Department under Grant 20K025 .
机构署名：
本校为第一机构
院系归属：
信息与电子工程学院
摘要：
Predicting associations between microRNAs (miRNAs) and diseases from the viewpoint of function modules has become increasingly popular. However, existing methods obtained the relations between diseases and miRNAs only through the construction of similarity networks and neglected the complex network characteristic. In this paper, a new method named combining miRNA function similarities and network topology similarities based on module identification in networks (ComSim-MINE) was developed. Combined similarity is calculated from the harmonic mean...
