Human interpretable grammar encodes multicellular systems biology models to democratize virtual cell laboratories Journal Article
| Authors: | Johnson, J. A. I.; Bergman, D. R.; Rocha, H. L.; Zhou, D. L.; Cramer, E.; Mclean, I. C.; Dance, Y. W.; Booth, M.; Nicholas, Z.; Lopez-Vidal, T.; Deshpande, A.; Heiland, R.; Bucher, E.; Shojaeian, F.; Dunworth, M.; Forjaz, A.; Getz, M.; Godet, I.; Kurtoglu, F.; Lyman, M.; Metzcar, J.; Mitchell, J. T.; Raddatz, A.; Solorzano, J.; Sundus, A.; Wang, Y.; DeNardo, D. G.; Ewald, A. J.; Gilkes, D. M.; Kagohara, L. T.; Kiemen, A. L.; Thompson, E. D.; Wirtz, D.; Wood, L. D.; Wu, P. H.; Zaidi, N.; Zheng, L.; Zimmerman, J. W.; Phillip, J. M.; Jaffee, E. M.; Gray, J. W.; Coussens, L. M.; Chang, Y. H.; Heiser, L. M.; Stein-O'Brien, G. L.; Fertig, E. J.; Macklin, P. |
| Article Title: | Human interpretable grammar encodes multicellular systems biology models to democratize virtual cell laboratories |
| Abstract: | Cells interact as dynamically evolving ecosystems. While recent single-cell and spatial multi-omics technologies quantify individual cell characteristics, predicting their evolution requires mathematical modeling. We propose a conceptual framework—a cell behavior hypothesis grammar—that uses natural language statements (cell rules) to create mathematical models. This enables systematic integration of biological knowledge and multi-omics data to generate in silico models, enabling virtual “thought experiments” that test and expand our understanding of multicellular systems and generate new testable hypotheses. This paper motivates and describes the grammar, offers a reference implementation, and demonstrates its use in developing both de novo mechanistic models and those informed by multi-omics data. We show its potential through examples in cancer and its broader applicability in simulating brain development. This approach bridges biological, clinical, and systems biology research for mathematical modeling at scale, allowing the community to predict emergent multicellular behavior. © 2025 The Authors |
| Keywords: | mathematical modeling; simulation; immunology; immunotherapy; mathematical biology; cancer biology; cell interactions; agent-based modeling; cell behaviors; multi-omics; spatial transcriptomics; cell behavior hypothesis grammar; modeling language; multicellular systems; multicellular systems biology; physics of multicellular biology; tissue dynamics |
| Journal Title: | Cell |
| Volume: | 188 |
| Issue: | 17 |
| ISSN: | 0092-8674 |
| Publisher: | Cell Press |
| Publication status: | Published |
| Date Published: | 2025-08-21 |
| Online Publication Date: | 2025-07-26 |
| Start Page: | 4711 |
| End Page: | 4733.e37 |
| Language: | English |
| DOI: | 10.1016/j.cell.2025.06.048 |
| PROVIDER: | scopus |
| PUBMED: | 40713951 |
| DOI/URL: | |
| Notes: | Article -- Source: Scopus |
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