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The Innovation Life > 2026 Vol. 4 > No. 3 > 100220
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From transcriptome reversal to network reprogramming: A new paradigm for drug screening driven by deep learning

  • 1.

    Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China

  • 2.

    Unilever R & D Shanghai, Shanghai 200335, China

  • 3.

    Guangzhou National Laboratory, Guangzhou 510000, China

  • 4.

    Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou Laboratory, Guangzhou Medical University, Guangzhou 510000, China

  • 5.

    Key Laboratory of Systems Health Science of Zhejiang Province, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China

  • 6.

    These authors contributed equally

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The Innovation Life  4(3),  https://doi.org/10.59717/j.xinn-life.2026.100220  |  Cite this article
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    • REFERENCES
  • [1] Xing J., Tan M., Leshchiner D., et al. (2026). Deep-learning-based de novo discovery and design of therapeutics that reverse disease-associated transcriptional phenotypes. Cell 189:2556−2572.e19. DOI:10.1016/j.cell.2026.02.016

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  • Cite this article:

    Yang Y., Zhang H., Li Y., et al. (2026). From transcriptome reversal to network reprogramming: A new paradigm for drug screening driven by deep learning. The Innovation Life 4:100220. https://doi.org/10.59717/j.xinn-life.2026.100220
    Yang Y., Zhang H., Li Y., et al. (2026). From transcriptome reversal to network reprogramming: A new paradigm for drug screening driven by deep learning. The Innovation Life 4:100220. https://doi.org/10.59717/j.xinn-life.2026.100220

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