Genomic language models could transform medicine but not yet
Recently, a genomic language model (gLM) with 40 billion parameters known as Evo2 has reached the same scale as the most powerful text large language models (LLMs). gLMs have been emerging as powerful tools to decode DNA sequences over the last five years. This article examines the emergence of gLMs and highlights Evo2 as a milestone in genomic language modeling, assessing both the scientific promise of gLMs and the practical challenges facing their implementation in medicine.
Authors
- Micaela Elisa Consens (ORCID: https://orcid.org/0000-0001-9918-2630)
- Ben Li (ORCID: https://orcid.org/0000-0002-6577-1872)
- Anna R. Poetsch (ORCID: https://orcid.org/0000-0003-3056-4360)
- Stephen Gilbert (ORCID: https://orcid.org/0000-0002-1997-1689)
Institutions
- University Health Network (CA)
- University of Toronto (CA)
- National Center for Tumor Diseases (DE)
- Vector Institute (CA)
- Center for Systems Biology Dresden (DE)
- Technische Universität Dresden (DE)
Publication Details
- Journal
- npj Digital Medicine
- Published
- 2025-04-18
- DOI
- https://doi.org/10.1038/s41746-025-01603-4
- Citations
- 11
- Primary Topic
- Genetics, Bioinformatics, and Biomedical Research
- Type
- article
- Field-Weighted Citation Impact
- 8.87
Funders
- University of Toronto
- Natural Sciences and Engineering Research Council of Canada