Scalable graph neural network for NMR chemical shift prediction
Jongmin Han, Hyungu Kang, Seokho Kang, Youngchun Kwon, Dongseon Lee, Youn-Suk Choi
Abstract
We present a scalable graph neural network (GNN) with improved message passing and readout functions for the fast and accurate prediction of nuclear magnetic resonance (NMR) chemical shifts.
Topics & Concepts
ScalabilityChemical shiftChemical spaceComputer scienceGraphNode (physics)Message passingRepresentation (politics)Molecular graphArtificial neural networkTheoretical computer scienceArtificial intelligenceChemistryDrug discoveryPhysicsDistributed computingDatabaseQuantum mechanicsPoliticsPhysical chemistryBiochemistryLawPolitical scienceMolecular spectroscopy and chiralityComputational Drug Discovery MethodsMetabolomics and Mass Spectrometry Studies