首页|Foundation models in molecular biology

Foundation models in molecular biology

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Determining correlations between molecules at various levels is an important topic in molecular biolo-gy.Large language models have demonstrated a remarkable ability to capture correlations from large amounts of data in the field of natural language processing as well as image generation,and correla-tions captured from data using large language models can also be applicable to solving a wide range of specific tasks,hence large language models are also referred to as foundation models.The massive amount of data that exists in the field of molecular biology provides an excellent basis for the develop-ment of foundation models,and the recent emergence of foundation models in the field of molecular bi-ology has really pushed the entire field forward.We summarize the foundation models developed based on RNA sequence data,DNA sequence data,protein sequence data,single-cell transcriptome da-ta,and spatial transcriptome data respectively,and further discuss the research directions for the de-velopment of foundation models in molecular biology.

Foundation modelsMolecular biologyTranscriptome

Yunda Si、Jiawei Zou、Yicheng Gao、Guohui Chuai、Qi Liu、Luonan Chen

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

Shanghai Institute of Biochemistry and Cell Biology,Center for Excellence in Molecular Cell Science,Chinese Academy of Sciences,University of Chinese Academy of Sciences,Shanghai 200031,China

Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine,Shanghai East Hos-pital,Frontier Science Center for Stem Cell Research,Bioinformatics Department,School of Life Sciences and Technology,Tongji University,Shanghai 200092,China

Shanghai Research Institute for Intelligent Autonomous Systems,Shanghai 201804,China

Key Laboratory of Systems Health Science of Zhejiang Province,School of Life Science,Hangzhou Institute for Ad-vanced Study,University of Chinese Academy of Sciences,Chinese Academy of Sciences,Hangzhou 310024,China

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2024

10.52601/bpr.2024.240006

生物物理学报告(英文)

生物物理学报告(英文)

ISSN：
年,卷(期)：2024.10(3)
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