Classification of substances by health hazard using deep neural networks and molecular electron densities

Classification of substances by health hazard using deep neural networks and molecular electron densities

Abstract In this paper we present a method that allows leveraging 3D electron density information to train a deep neural network pipeline to segment regions of high, medium and low electronegativity and classify substances as health hazardous or non-hazardous. We show that this can be used for use-c...

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Bibliographic Details
Main Authors: Satnam Singh, Gina Zeh, Jessica Freiherr, Thilo Bauer, Isik Türkmen, Andreas T. Grasskamp
Format: Article
Language:English
Published: BMC 2024-04-01
Series:Journal of Cheminformatics
Subjects:
Electron density
Machine learning
Computational chemistry
Health hazard
3D-UNet
Online Access:https://doi.org/10.1186/s13321-024-00835-y

Internet

https://doi.org/10.1186/s13321-024-00835-y

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