REDDA: Integrating multiple biological relations to heterogeneous graph neural network for drug-disease association prediction-Reference-Cited by-同舟云学术

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REDDA: Integrating multiple biological relations to heterogeneous graph neural network for drug-disease association prediction

Published:2022-11 Issue: Volume:150 Page:106127
ISSN:0010-4825
Container-title:Computers in Biology and Medicine
language:en
Short-container-title:Computers in Biology and Medicine

Author:

Gu Yaowen^ORCID,Zheng Si,Yin Qijin^ORCID,Jiang Rui,Li Jiao^ORCID

Funder

National Natural Science Foundation of China

Ministry of Science and Technology of the People's Republic of China

Chinese Academy of Medical Sciences

National Key Research and Development Program of China

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications

Reference68 articles.

1. Advancing drug discovery via artificial intelligence;Chan;Trends Pharmacol. Sci.,2019

2. Research and development spending to bring a single cancer drug to market and revenues after approval;Prasad;JAMA Intern. Med.,2017

3. Innovation in the pharmaceutical industry: new estimates of R&D costs;DiMasi;J. Health Econ.,2016

4. Estimation of clinical trial success rates and related parameters;Wong;Biostatistics,2019

5. Applications of machine learning in drug discovery and development;Vamathevan;Nat. Rev. Drug Discov.,2019

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