Drug-Target Interactions Prediction Based on Signed Heterogeneous Graph Neural Networks-Reference-Cited by-同舟云学术

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Drug-Target Interactions Prediction Based on Signed Heterogeneous Graph Neural Networks

Published:2024-01 Issue:1 Volume:33 Page:231-244
ISSN:2075-5597
Container-title:Chinese Journal of Electronics
language:
Short-container-title:Chinese J. Elect.

Author:

Chen Ming¹,Jiang Yajian¹,Lei Xiujuan²,Pan Yi³,Ji Chunyan⁴,Jiang Wei¹

Affiliation:

1. College of Information Science and Engineering, Hunan Normal University,Changsha,China,410081

2. School of Computer Science, Shaanxi Normal University,Xi'an,China,710119

3. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences,Faculty of Computer Science and Control Engineering,Shenzhen,China,518055

4. BNU-HKBU United International College,Computer Science Department,Zhuhai,China,519087

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/9970761/10410587/10410581.pdf?arnumber=10410581

Reference45 articles.

1. Current status and future prospects of drug–target interaction prediction

2. Drug–target interaction prediction: databases, web servers and computational models

3. Drug-pathway association prediction: from experimental results to computational models

4. Recent Advances in the Machine Learning-Based Drug-Target Interaction Prediction

5. Association predictions of genomics, proteinomics, transcriptomics, microbiome, metabolomics, pathomics, radiomics, drug, symptoms, environment factor, and disease networks: A comprehensive approach

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