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US 2025/0061979 A1Published application
Predicting molecule properties using graph neural network
AssigneeKebotix, Inc.
InventorsDennis Sheberla, Kevin Ryan
Life of this patent
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AssigneeKebotix, Inc.
InventorsDennis Sheberla, Kevin Ryan
Estimating the term…
The techniques described herein relate to computerized methods and apparatuses for predicting properties of molecules using a neural network. The neural network may include one or more layers to convert atom and bond features of an input molecule into respective atom and bond representations; a graph neural network configured to update the atom and bond representations; a molecule layer configured to convert the updated atom and bond representations into a molecule representation; and a target layer configured to predict one or more properties of the molecule based on the molecule representation. Prediction may include a regression operation to predict a single property value of the molecule, or a classification operation to predict probabilities of the molecule belonging to respective classes of a plurality of classes. The graph neural network may include a graph transformer network. The graph neural network may include a graph convolutional neural network.
A system for predicting properties of a molecule, the system comprising:
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A method for predicting properties of a molecule, the method comprising, using at least one processor:
22-40. (canceled)
A non-transitory computer-readable media comprising instructions that, when executed, cause at least one processor to perform operations comprising:
42-45. (canceled)
Dependencies are inferred from the claim text.