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COMPUTATIONAL DRUG SCREENING

Learning the missing channel

Nature Machine Intelligence volume 4, pages 616–617 (2022)Cite this article

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Microscopy-based drug screens with fluorescent markers can shed light on how drugs affect biological processes. Without adding markers and imaging channels, which is cumbersome and costly, a new generative deep-learning method extracts new fluorescence channels from images, potentially improving the drug-discovery pipeline.

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Fig. 1: Trans-channel fluorescence learning by an encoder–decoder network enhances drug discovery.

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Authors and Affiliations

  1. Division of Signaling and Functional Genomics, German Cancer Research Center, Heidelberg, Germany

    Florian Heigwer

  2. Department of Cell and Molecular Biology, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany

    Florian Heigwer

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  1. Florian Heigwer
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Correspondence to Florian Heigwer.

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The author declares no competing interests.

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Heigwer, F. Learning the missing channel. Nat Mach Intell 4, 616–617 (2022). https://doi.org/10.1038/s42256-022-00514-3

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