FIGURE

Fig 1

ID

ZDB-FIG-210802-28

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 1

Regression generator diagram.

Schematic representation of Go-ZT architecture showing chemical structural input represented as weights (w_i) and views (v_i) matrices passed through two fully connected neural networks to produce a predicted toxicity matrix. Darker matrix shading indicates higher toxicity values.

Expression Data

Expression Detail

Antibody Labeling

Phenotype Data

Phenotype Detail

Acknowledgments

This image is the copyrighted work of the attributed author or publisher, and ZFIN has permission only to display this image to its users. Additional permissions should be obtained from the applicable author or publisher of the image. Full text @ PLoS Comput. Biol.