DeepKinome: quantitative prediction of kinase binding affinity by a compound using deep learning based regression model

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Journal
Frontiers in Molecular Biosciences
Published
2025-12-17
DOI
https://doi.org/10.3389/fmolb.2025.1698891
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00

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article

DeepKinome: quantitative prediction of kinase binding affinity by a compound using deep learning based regression model

Jong Seon Eun, Seungyoon Nam, Jinhyuk Lee, Yeeun Lee
Frontiers in Molecular Biosciences
Computational Drug Discovery Methods
article

DeepKinome: quantitative prediction of kinase binding affinity by a compound using deep learning based regression model

Jong Seon Eun, Seungyoon Nam, Jinhyuk Lee, Yeeun Lee
article en

Abstract

No abstract available for this paper.
Frontiers in Molecular BiosciencesVol. 12
Gachon University (KR), Korea Research Institute of Bioscience and Biotechnology (KR), Korea University of Science and Technology (KR)
National Research Foundation, Korea Research Institute of Bioscience and Biotechnology, National Research Foundation of Korea, Ministry of Science and ICT, South Korea
Openalex Percentile: Top 60%
Computational Drug Discovery Methods
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DeepKinome: quantitative prediction of kinase binding affinity by a compound using deep learning based regression model — Jong Seon Eun, Seungyoon Nam, et al. · Frontiers in Molecular Biosciences (2025) | TGRS Research Map | TGRS