Network-based multi-omics integrative analysis methods in drug discovery: a systematic review
Hubei University · Sun Yat-sen University
Abstract
The integration of multi-omics data from diverse high-throughput technologies has revolutionized drug discovery. While various network-based methods have been developed to integrate multi-omics data, systematic evaluation and comparison of these methods remain challenging. This review aims to analyze network-based approaches for multi-omics integration and evaluate their applications in drug discovery. We conducted a comprehensive review of literature (2015-2024) on network-based multi-omics integration methods in drug discovery, and categorized methods into four primary types: network propagation/diffusion, similarity-based approaches, graph neural networks, and network inference models. We also discussed the…
Citation impact
- FWCI
- 38.21
- Percentile
- 100%
- References
- 132
Authors
4Topics & keywords
- Computer science
- Data science
- Drug discovery
- Omics
- Computational biology
- Data mining
- Bioinformatics
- Biology