Deep Learning in Drug Design: Protein-Ligand Binding Affinity Prediction is a research paper published in IEEE/ACM Transactions on Computational Biology and Bioinformatics (2020). On theSindex it has a DataRank of 0. It has been cited 86 times.
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National Science Foundation
Grant: CNS-1842407
National Institutes of Health
Grant: R01GM110240
National Institutes of Health
Grant: R01NS088437
National Institutes of Health
Grant: R01CA212403
National Institutes of Health
Grant: 5R01NS088437-04
Small molecule in vivo probe development targeting the IL-6/STAT3 pathway for potential multiple sclerosis therapy
National Institutes of Health
Grant: 1R01GM110240-01A1
Integrating data, algorithms and clinical reasoning for surgical risk assessment
National Institutes of Health
Grant: 5R01CA212403-05
Role and targeting of PRMT5 in prostate cancer
FWCI
4.31
Citation Percentile
1.0%
Influential Citations
3
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals
Additional file 1 of Structure-based, deep-learning models for protein-ligand binding affinity prediction
Additional file 1 of Structure-based, deep-learning models for protein-ligand binding affinity prediction