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Large-language models facilitate discovery of the molecular signatures regulating sleep and activity

Author

Listed:
  • Di Peng

    (Huazhong University of Science and Technology)

  • Liubin Zheng

    (Huazhong University of Science and Technology)

  • Dan Liu

    (Huazhong University of Science and Technology)

  • Cheng Han

    (Huazhong University of Science and Technology)

  • Xin Wang

    (Huazhong University of Science and Technology)

  • Yan Yang

    (Huazhong University of Science and Technology)

  • Li Song

    (Huazhong University of Science and Technology)

  • Miaoying Zhao

    (Huazhong University of Science and Technology)

  • Yanfeng Wei

    (Huazhong University of Science and Technology)

  • Jiayi Li

    (Huazhong University of Science and Technology)

  • Xiaoxue Ye

    (Huazhong University of Science and Technology)

  • Yuxiang Wei

    (Huazhong University of Science and Technology)

  • Zihao Feng

    (Huazhong University of Science and Technology)

  • Xinhe Huang

    (Huazhong University of Science and Technology)

  • Miaomiao Chen

    (Huazhong University of Science and Technology)

  • Yujie Gou

    (Huazhong University of Science and Technology)

  • Yu Xue

    (Huazhong University of Science and Technology
    Nanjing University Institute of Artificial Intelligence Biomedicine)

  • Luoying Zhang

    (Huazhong University of Science and Technology
    Hubei Province Key Laboratory of Oral and Maxillofacial Development and Regeneration)

Abstract

Sleep, locomotor and social activities are essential animal behaviors, but their reciprocal relationships and underlying mechanisms remain poorly understood. Here, we elicit information from a cutting-edge large-language model (LLM), generative pre-trained transformer (GPT) 3.5, which interprets 10.2–13.8% of Drosophila genes known to regulate the 3 behaviors. We develop an instrument for simultaneous video tracking of multiple moving objects, and conduct a genome-wide screen. We have identified 758 fly genes that regulate sleep and activities, including mre11 which regulates sleep only in the presence of conspecifics, and NELF-B which regulates sleep regardless of whether conspecifics are present. Based on LLM-reasoning, an educated signal web is modeled for understanding of potential relationships between its components, presenting comprehensive molecular signatures that control sleep, locomotor and social activities. This LLM-aided strategy may also be helpful for addressing other complex scientific questions.

Suggested Citation

  • Di Peng & Liubin Zheng & Dan Liu & Cheng Han & Xin Wang & Yan Yang & Li Song & Miaoying Zhao & Yanfeng Wei & Jiayi Li & Xiaoxue Ye & Yuxiang Wei & Zihao Feng & Xinhe Huang & Miaomiao Chen & Yujie Gou , 2024. "Large-language models facilitate discovery of the molecular signatures regulating sleep and activity," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-48005-w
    DOI: 10.1038/s41467-024-48005-w
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    References listed on IDEAS

    as
    1. Wanhe Li & Zikun Wang & Sheyum Syed & Cheng Lyu & Samantha Lincoln & Jenna O’Neil & Andrew D. Nguyen & Irena Feng & Michael W. Young, 2021. "Chronic social isolation signals starvation and reduces sleep in Drosophila," Nature, Nature, vol. 597(7875), pages 239-244, September.
    2. Tyna Eloundou & Sam Manning & Pamela Mishkin & Daniel Rock, 2023. "GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models," Papers 2303.10130, arXiv.org, revised Aug 2023.
    3. Diogo Pimentel & Jeffrey M. Donlea & Clifford B. Talbot & Seoho M. Song & Alexander J. F. Thurston & Gero Miesenböck, 2016. "Operation of a homeostatic sleep switch," Nature, Nature, vol. 536(7616), pages 333-337, August.
    4. Fumika N. Hamada & Mark Rosenzweig & Kyeongjin Kang & Stefan R. Pulver & Alfredo Ghezzi & Timothy J. Jegla & Paul A. Garrity, 2008. "An internal thermal sensor controlling temperature preference in Drosophila," Nature, Nature, vol. 454(7201), pages 217-220, July.
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