Drug–target affinity prediction using graph neural network and contact maps
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Prediction of drug–target affinity by constructing both molecule and protein graphs.
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Spatial molecular profiling can measure gene expression at the cellular level and the location of cells in a tissue.
“Spatial molecular profiling can measure both gene expression at the cellular level and location of cells in a tissue [160].”
From Graph representation learning in biomedicine and healthcare (2022) · cites this paper as [160]
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References 61 · Cited by 372
Research works printed but not linked: 7
- Salomon-Ferrer R. Case D. A. Walker R. C. Wiley Interdiscip. Rev.: Comput. Mol. Sci. 2013 3 198 210
- Bashir M. Y., Muneer K., Mustafa R. and Rehman H. U., in 2019 15th International Conference on Emerging Technologies, ICET, 2019, pp. 1–6
- Veličković P., Cucurull G., Casanova A., Romero A., Lio P. and Bengio Y., 2017, arXiv Prepr. arXiv:1710.10903 · arXiv
- Feng Q., Dueva E., Cherkasov A. and Ester M., 2018, arXiv Prepr. arXiv:1807.09741 · arXiv
- Nguyen T. Le H. Venkatesh S. bioRxiv 2019 684662
- Ronneberger O., Fischer P. and Brox T., in International Conference on Medical image computing and computer-assisted intervention, 2015, pp. 234–241
- cheol J. J. Lin X. Chen X.-W. IEEE/ACM Trans. Comput. Biol. Bioinf. 2010 8 2 308 315 20855926
- Authors
- Jiang, M., Li, Z., Zhang, S., Wang, S., Wang, X., Yuan, Q., & Wei, Z.
- Affiliations
- Ocean University of China (CN)
- Corresponding author
- Li, Zhen
- Venue
- RSC Advances
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2020
- Volume
- 10
- Issue
- 35
- Pages
- 20701-20712
- ISSN
- 2046-2069 (ISSN-L)
- PMC
- PMC9054320
- OpenAlex
- W3032123378
- Cited by
- 372
- References
- 61
- Citations by year
- 2026: 50 · 2025: 97 · 2024: 78 · 2023: 55 · 2022: 46 · 2021: 42 · 2020: 3
- FWCI
- 18.10
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- RSC Advances (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Funders
- The National Key Research and Development Program of China (2019YFD0900401)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Degradation and Inhibitors
- Keywords
- drug-target affinity prediction, graph neural networks, contact maps, protein contact prediction, protein structure prediction from sequence, molecular graphs, computer-aided drug design
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