Heterogeneous networks in drug-target interaction prediction

Mohammad Molaee, Nasrollah Moghadam Charkari, Foad Ghaderi
4/22/2025
q-bio.BMcs.AIcs.LG

No official code found. Best implementation: luoyunan/DTINet (189 stars, GPL-3.0, last commit 2022-10-30). 2 more below.

Abstract

Drug discovery requires a tremendous amount of time and cost. Computational drug-target interaction prediction, a significant part of this process, can reduce these requirements by narrowing the search space for wet lab experiments. In this survey, we provide comprehensive details of graph machine learning-based methods in predicting drug-target interaction, as they have shown promising results in this field. These details include the overall framework, main contribution, datasets, and their source codes. The selected papers were mainly published from 2020 to 2024. Prior to discussing papers, we briefly introduce the datasets commonly used with these methods and measurements to assess their performance. Finally, future challenges and some crucial areas that need to be explored are discussed.

View on arXivView PDF

Code Implementations(3)

luoyunan/DTINetCommunity100%
GPL-3.0

A Network Integration Approach for Drug-Target Interaction Prediction

18960M, ShellSep 28, 20163 years agoGPL-3.0
MedicineBiology-AI/EEG-DTICommunity100%

An end-to-end heterogeneous graph representation learning-based framework for drug-target interaction prediction

318PythonOct 15, 20204 years ago
ahu-bioinf-lab/AMGDTICommunity100%

A Network Integration Approach for Drug-Target Interaction Prediction

132PythonApr 12, 20231 years ago
adaptive-meta-graphgraph-convolutional-networksheterogeneous-network

Similar Papers

Drug-Target Interaction/Affinity Prediction: Deep Learning Models and Advances Review

90% match2025

A Graph-in-Graph Learning Framework for Drug-Target Interaction Prediction

90% match2025

Comprehensive evaluation of deep and graph learning on drug-drug interactions prediction

88% match1 repo302023

Emerging Drug Interaction Prediction Enabled by Flow-based Graph Neural Network with Biomedical Network

87% match1 repo302023

A Survey of Graph Neural Networks for Drug Discovery: Recent Developments and Challenges

87% match2025

A Heterogeneous Network-based Contrastive Learning Approach for Predicting Drug-Target Interaction

87% match1 repo42024

Cite this paper

@article{molaee2025heterogeneous,
  title  = {Heterogeneous networks in drug-target interaction prediction},
  author = {Mohammad Molaee and Nasrollah Moghadam Charkari and Foad Ghaderi},
  year   = {2025},
  eprint = {2504.16152},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2504.16152v2}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2504.16152.svg)](https://codeofpaper.com/paper/2504.16152)

Discussion