Large Language Models in Plant Biology

Hilbert Yuen In Lam, Xing Er Ong, Marek Mutwil
1/5/2024
q-bio.GNcs.CL

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Abstract

Large Language Models (LLMs), such as ChatGPT, have taken the world by storm and have passed certain forms of the Turing test. However, LLMs are not limited to human language and analyze sequential data, such as DNA, protein, and gene expression. The resulting foundation models can be repurposed to identify the complex patterns within the data, resulting in powerful, multi-purpose prediction tools able to explain cellular systems. This review outlines the different types of LLMs and showcases their recent uses in biology. Since LLMs have not yet been embraced by the plant community, we also cover how these models can be deployed for the plant kingdom.

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@article{lam2024large,
  title  = {Large Language Models in Plant Biology},
  author = {Hilbert Yuen In Lam and Xing Er Ong and Marek Mutwil},
  year   = {2024},
  eprint = {2401.02789},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2401.02789v1}
}

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