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Liu, Ran, Liu, Xiang, Wu, Jie (2023) Persistent Path-Spectral (PPS) Based Machine Learning for Protein–Ligand Binding Affinity Prediction. Journal of Chemical Information and Modeling, 63 (3) 1066-1075 doi:10.1021/acs.jcim.2c01251

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Reference TypeJournal (article/letter/editorial)
TitlePersistent Path-Spectral (PPS) Based Machine Learning for Protein–Ligand Binding Affinity Prediction
JournalJournal of Chemical Information and Modeling
AuthorsLiu, RanAuthor
Liu, XiangAuthor
Wu, JieAuthor
Year2023 (February 13)Volume63
Issue3
PublisherAmerican Chemical Society (ACS)
DOIdoi:10.1021/acs.jcim.2c01251Search in ResearchGate
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Mindat Ref. ID15705440Long-form Identifiermindat:1:5:15705440:0
GUID0
Full ReferenceLiu, Ran, Liu, Xiang, Wu, Jie (2023) Persistent Path-Spectral (PPS) Based Machine Learning for Protein–Ligand Binding Affinity Prediction. Journal of Chemical Information and Modeling, 63 (3) 1066-1075 doi:10.1021/acs.jcim.2c01251
Plain TextLiu, Ran, Liu, Xiang, Wu, Jie (2023) Persistent Path-Spectral (PPS) Based Machine Learning for Protein–Ligand Binding Affinity Prediction. Journal of Chemical Information and Modeling, 63 (3) 1066-1075 doi:10.1021/acs.jcim.2c01251
In(2023, February) Journal of Chemical Information and Modeling Vol. 63 (3) American Chemical Society (ACS)

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