Exploring the intersection of mechanobiology and artificial intelligence
The rapid increase in cell biology techniques, combined with high-throughput technologies and improved computing, has yielded complex data that classical methods struggle to analyze. The question arises, can a machine overcome human performance to identify and predict distinct biological scenarios? Here, we review the mechanotransduction of extracellular matrix mechanical cues and how Artificial Intelligence-based methodologies are or can be used to predict cell states based on morphological and genetic signatures.
Authors
- Kashish Jain (ORCID: https://orcid.org/0000-0002-4990-9333)
- Valerie M. Weaver (ORCID: https://orcid.org/0000-0003-4786-6752)
- Roger Oria (ORCID: https://orcid.org/0000-0002-5974-9775)
Institutions
- University of California, San Francisco (US)
- California Institute for Regenerative Medicine (US)
- Broad Center (US)
- UCSF Helen Diller Family Comprehensive Cancer Center (US)
Publication Details
- Journal
- npj Biological Physics and Mechanics.
- Published
- 2025-03-26
- DOI
- https://doi.org/10.1038/s44341-025-00010-w
- Citations
- 6
- Primary Topic
- Cellular Mechanics and Interactions
- Type
- article
- Field-Weighted Citation Impact
- 6.91
Funders
- U.S. Department of Defense
- National Foundation for Cancer Research
- Mark Foundation For Cancer Research