版权说明 操作指南
首页 > 成果 > 成果详情

SVMMDR: Prediction of miRNAs-drug resistance using support vector machines based on heterogeneous network

认领
导出
Link by DOI
反馈
分享
QQ微信 微博
成果类型:
期刊论文
作者:
Duan, Tao;Kuang, Zhufang;Deng, Lei
通讯作者:
Kuang, Z.
作者机构:
[Deng, Lei; Duan, Tao; Kuang, Zhufang] Cent South Univ Forestry & Technol, Sch Comp & Informat Engn, Changsha, Peoples R China.
通讯机构:
[Kuang, Z.] S
School of Computer and Information Engineering, China
语种:
英文
关键词:
miRNA;Drug Resistance;Support Vector Machines;HeteSim score;random walk with restart
期刊:
FRONTIERS IN ONCOLOGY
ISSN:
2234-943X
年:
2022
卷:
12
页码:
987609
基金类别:
This work was supported in part by the National Natural Science Foundation of China under Grants Nos. 62072477, 61309027, 61702562 and 61702561, the Hunan Provincial Natural Science Foundation of China under Grants No.2018JJ3888, the Scientific Research Fund of Hunan Provincial Education Department under Grant No.18B197, the National Key R&D Program of China under Grant No.2018YFB1700200, the Open Research Project of Key Laboratory of Intelligent Information Perception and Processing Technology (Hunan Province) under Grant No.2017KF01, the Hunan Key Laboratory of Intelligent Logistics Technology 2019TP1015.
机构署名:
本校为第一机构
院系归属:
计算机与信息工程学院
摘要:
In recent years, the miRNA is considered as a potential high-value therapeutic target because of its complex and delicate mechanism of gene regulation. The abnormal expression of miRNA can cause drug resistance, affecting the therapeutic effect of the disease. Revealing the associations between miRNAs-drug resistance can help in the design of effective drugs or possible drug combinations. However, current conventional experiments for identification of miRNAs-drug resistance are time-consuming and high-cost. Therefore, it’s of pretty realistic ...

反馈

验证码:
看不清楚,换一个
确定
取消

成果认领

标题:
用户 作者 通讯作者
请选择
请选择
确定
取消

提示

该栏目需要登录且有访问权限才可以访问

如果您有访问权限,请直接 登录访问

如果您没有访问权限,请联系管理员申请开通

管理员联系邮箱:yun@hnwdkj.com