Novel deep learning model for more accurate prediction of drug-drug interaction effects-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Novel deep learning model for more accurate prediction of drug-drug interaction effects

Published:2019-08-06 Issue:1 Volume:20 Page:
ISSN:1471-2105
Container-title:BMC Bioinformatics
language:en
Short-container-title:BMC Bioinformatics

Author:

Lee Geonhee,Park Chihyun,Ahn Jaegyoon^ORCID

Funder

Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education

Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Structural Biology

Link

http://link.springer.com/content/pdf/10.1186/s12859-019-3013-0.pdf

Reference27 articles.

1. Foucquier J, Guedj M. Analysis of drug combinations: current methodological landscape. Pharmacol Res Perspect. 2015;3(3):e00149.

2. Edwards IR, Aronson JK. Adverse drug reactions: definitions, diagnosis, and management. Lancet. 2000;356(9237):1255–9.

3. Tatonetti NP, Fernald GH, Altman RB. A novel signal detection algorithm for identifying hidden drug-drug interactions in adverse event reports. J Am Med Inform Assoc. 2011, 19(1):79–85.

4. Pirmohamed M, Orme M: Drug interactions of clinical importance. Davies’s textbook of adverse drug reactions 1998:888–912.

5. Onakpoya IJ, Heneghan CJ, Aronson JK. Post-marketing withdrawal of 462 medicinal products because of adverse drug reactions: a systematic review of the world literature. BMC Med. 2016;14(1):10.

Cited by 93 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. A study on improving drug–drug interactions prediction using convolutional neural networks;Applied Soft Computing;2024-11

2. FSRM-DDIE : few-shot learning methods based on relation metrics for the prediction of drug-drug interaction events;Applied Intelligence;2024-09-10

3. MTrans: M-Transformer and Knowledge Graph-Based Network for Predicting Drug–Drug Interactions;Electronics;2024-07-25

4. BiRNN-DDI: A Drug-Drug Interaction Event Type Prediction Model Based on Bidirectional Recurrent Neural Network and Graph2Seq Representation;Journal of Computational Biology;2024-07-25

5. MathEagle: Accurate prediction of drug-drug interaction events via multi-head attention and heterogeneous attribute graph learning;Computers in Biology and Medicine;2024-07

同舟云学术

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