RegioML: predicting the regioselectivity of electrophilic aromatic substitution reactions using machine learning
Nicolai Ree, Andreas H. Göller, Jan H. Jensen
Abstract
We present RegioML, an atom-based machine learning model for predicting the regioselectivities of electrophilic aromatic substitution reactions.
Topics & Concepts
RegioselectivityElectrophilic aromatic substitutionElectrophilic substitutionElectrophileSubstitution (logic)Substitution reactionChemistryComputer scienceArtificial intelligenceCombinatorial chemistryOrganic chemistryProgramming languageCatalysisMachine Learning in Materials ScienceComputational Drug Discovery MethodsChemical Synthesis and Analysis