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Multimodal large language models for bioimage analysis

Nature Methods volume 21, pages 1390–1393 (2024)Cite this article

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Multimodal large language models have been recognized as a historical milestone in the field of artificial intelligence and have demonstrated revolutionary potentials not only in commercial applications, but also for many scientific fields. Here we give a brief overview of multimodal large language models through the lens of bioimage analysis and discuss how we could build these models as a community to facilitate biology research.

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Fig. 1: Constructing MLLMs for bioimage analysis.
Fig. 2: An example of applying MLLMs to bioimage analysis.

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Acknowledgements

S.Z. is supported by the National Science and Technology Major Project of China (No. 2022ZD0117801). J.C. is funded by the Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung, BMBF) in Germany under the funding reference 161L0272, and also supported by the Ministry of Culture and Science of the State of North Rhine-Westphalia (Ministerium für Kultur und Wissenschaft des Landes Nordrhein-Westfalen, MKW NRW).

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Authors and Affiliations

  1. State Key Laboratory of Multimedia Information Processing, School of Computer Science, Peking University, Beijing, China

    Shanghang Zhang, Gaole Dai & Tiejun Huang

  2. Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V., Dortmund, Germany

    Jianxu Chen

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  1. Shanghang Zhang
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  2. Gaole Dai
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Contributions

S.Z. proposed the idea and paper framework, and G.D., T.H. & J.C. joined the discussion. All the authors wrote, edited and gave final approval to the manuscript.

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Correspondence to Shanghang Zhang or Jianxu Chen.

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Zhang, S., Dai, G., Huang, T. et al. Multimodal large language models for bioimage analysis. Nat Methods 21, 1390–1393 (2024). https://doi.org/10.1038/s41592-024-02334-2

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