Graph Regularized Probabilistic Matrix Factorization for Drug-Drug Interactions Prediction
Author:
Affiliation:
1. CVN, Inria Saclay, University Paris Saclay, Gif-sur-Yvette, France
2. Department of ECE, IIIT - Delhi, Delhi, India
Funder
European Research Council Starting
Associate Team COMPASS between Inria and IIIT Delhi
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics
Link
http://xplorestaging.ieee.org/ielx7/6221020/10116032/10048531.pdf?arnumber=10048531
Reference51 articles.
1. Detection of drug–drug interactions through data mining studies using clinical sources, scientific literature and social media
2. Drug-drug interaction software in clinical practice: a systematic review
3. Similarity-based modeling in large-scale prediction of drug-drug interactions
4. DDI-CPI, a server that predicts drug–drug interactions through implementing the chemical–protein interactome
5. Predicting Comprehensive Drug-Drug Interactions for New Drugs via Triple Matrix Factorization
Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Drug repositioning based on tripartite cross-network embedding and graph convolutional network;Expert Systems with Applications;2024-10
2. HPTRMF: Collaborative Matrix Factorization-Based Prediction Method for LncRNA-Disease Associations Using High-Order Perturbation and Flexible Trifactor Regularization;Journal of Chemical Information and Modeling;2024-07-26
3. MathEagle: Accurate prediction of drug-drug interaction events via multi-head attention and heterogeneous attribute graph learning;Computers in Biology and Medicine;2024-07
4. AutoDDI: Drug–Drug Interaction Prediction With Automated Graph Neural Network;IEEE Journal of Biomedical and Health Informatics;2024-03
5. Enhancing drug discovery in schizophrenia: a deep learning approach for accurate drug-target interaction prediction – DrugSchizoNet;Computer Methods in Biomechanics and Biomedical Engineering;2024-02-20
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3