FIGURE
Fig 2
- ID
- ZDB-FIG-210802-29
- Publication
- Green et al., 2021 - Leveraging high-throughput screening data, deep neural networks, and conditional generative adversarial networks to advance predictive toxicology
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Fig 2
Schematic representation of GAN-ZT architecture showing chemical structural input represented as weights (wi) and views (vi) matrices passed through two fully connected neural networks to produce a predicted toxicity matrix. Chemical features along with predicted or empirical toxicity matrices are then passed to a discriminator comprising a fully-connected neural network. Darker matrix shading indicates higher toxicity values. |
Expression Data
Expression Detail
Antibody Labeling
Phenotype Data
Phenotype Detail
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Full text @ PLoS Comput. Biol.