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Fig. 2

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ZDB-FIG-250822-29

Publication

Zhang et al., 2025 - Deep learning enhanced deciphering of brain activity maps for discovery of therapeutics for brain disorders

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Fig. 2

Development of the DeepBAM platform (A) There are a total of 451 compounds, including the training set (330 drugs with ATC code) and the test set (121 compounds without ATC code). The distribution of the drug library containing clinically used drugs with ATC codes and nonclinical compounds. The abbreviations for different ATC categories are A for the alimentary tract and metabolism, C for the cardiovascular system, M for the musculoskeletal system, N for the nervous system, R for the respiratory system, S for sensory organs, V for various other drugs. Non-ATC indicates non-clinical compounds without any ATC codes. (B) Schematic figure showing the build of deep convolutional autoencoder for comprehensive feature learning from T-score BAMs. (C) Implementation of unsupervised clustering for discovering subgroups and deep neural network for predicting identified subgroups.

Expression Data

Expression Detail

Antibody Labeling

Phenotype Data

Phenotype Detail

Acknowledgments

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