Predicting Drug-Protein Interactions by Self-Adaptively Adjusting the Topological Structure of the Heterogeneous Network-Reference-Cited by-同舟云学术

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Predicting Drug-Protein Interactions by Self-Adaptively Adjusting the Topological Structure of the Heterogeneous Network

Published:2023-11 Issue:11 Volume:27 Page:5675-5684
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Tang Rong¹^ORCID,Sun Chang¹^ORCID,Huang Jipeng¹^ORCID,Li Minglei¹^ORCID,Wei Jinmao¹^ORCID,Liu Jian¹^ORCID

Affiliation:

1. College of Computer Science, Nankai University, Tianjin, China

Funder

National Key R&D Programs of China

Natural Science Foundation of Tianjin City

Graduate Research Innovation Foundation of Tianjin City

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/ielx7/6221020/10311342/10241994.pdf?arnumber=10241994

Reference43 articles.

1. Comparing methods for drug–gene interaction prediction on the biomedical literature knowledge graph: performance versus explainability

2. MONN: A Multi-objective Neural Network for Predicting Compound-Protein Interactions and Affinities

3. Keynote review: In vitro safety pharmacology profiling: an essential tool for successful drug development

4. An integrative drug repositioning framework discovered a potential therapeutic agent targeting COVID-19

5. Machine learning approaches and databases for prediction of drug–target interaction: a survey paper

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