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Synergy and Complementarity between Focused Machine Learnin..:

Ann E. Cleves (10313490) ; Stephen R. Johnson (2238253) ; Ajay N. Jain (1270995)
https://figshare.com/articles/dataset/Synergy_and_Complementarity_between_Focused_Machine_Learning_and_Physics-Based_Simulation_in_Affinity_Prediction/17161025. , 2021

Link: https://doi.org/10.1021/acs.jcim.1c01382.s002

RT Journal
T1 <Title>Synergy and Complementarity between Focused Machine Learning and Physics-Based Simulation in Affinity Prediction</Title>

UL https://suche.suub.uni-bremen.de/peid=base-ftsmithonian:oai:figshare.com:article_17161025&Exemplar=1&LAN=DE
				
A1 Ann E. Cleves (10313490)
A1 Stephen R. Johnson (2238253)
A1 Ajay N. Jain (1270995)
YR 2021
K1 Biochemistry
K1 Biological Sciences not elsewhere classified
K1 Mathematical Sciences not elsewhere classified
K1 Information Systems not elsewhere classified
K1 sup >+</ sup
K1 original series publications
K1 ligand affinity prediction
K1 hybrid prediction strategies
K1 focused machine learning
K1 accurate quansa models
K1 affinity prediction
K1 machine learning
K1 hybrid model
K1 accurate within
K1 results argue
K1 results across
K1 relevant ligands
K1 present results
K1 makes use
K1 k </
K1 either method
K1 based simulation
K1 appropriate compounds
K1 applied carefully
K1 applicable domain
K1 absolute p
K1 >< sub
K1 </ sub
K1 1 inhibitors
JF https://figshare.com/articles/dataset/Synergy_and_Complementarity_between_Focused_Machine_Learning_and_Physics-Based_Simulation_in_Affinity_Prediction/17161025
LK http://dx.doi.org/https://doi.org/10.1021/acs.jcim.1c01382.s002
DO https://doi.org/10.1021/acs.jcim.1c01382.s002
SF ELIB - SuUB Bremen

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