Human interpretable grammar encodes multicellular systems biology models to democratize virtual cell laboratoriesWe developed a plain text modeling language—a cell behavior hypothesis grammar—to easily build virtual cell models and connect them to data, helping scientists to unlock the hidden dynamics of tissues. We provide examples showing how to use them in virtual experiments exploring how cancer responds to the cells in its environment and how the brain forms layers in development.We developed a plain text modeling language—a cell behavior hypothesis grammar—to easily build virtual cell models and connect them to data, helping scientists to unlock the hidden dynamics of tissues. We provide examples showing how to use them in virtual experiments exploring how cancer responds to the cells in its environment and how the brain forms layers in development.Jeanette A.I. Johnson, Daniel R. Bergman, Heber L. Rocha, David L. Zhou, Eric Cramer, Ian C. Mclean, Yoseph W. Dance, Max Booth, Zachary Nicholas, Tamara Lopez-Vidal, Atul Deshpande, Randy Heiland, Elmar Bucher, Fatemeh Shojaeian, Matthew Dunworth, André Forjaz, Michael Getz, Inês Godet, Furkan Kurtoglu, Melissa Lyman, John Metzcar, Jacob T. Mitchell, Andrew Raddatz, Jacobo Solorzano, Aneequa Sundus, Yafei Wang, David G. DeNardo, Andrew J. Ewald, Daniele M. Gilkes, Luciane T. Kagohara, Ashley L. Kiemen, Elizabeth D. Thompson, Denis Wirtz, Laura D. Wood, Pei-Hsun Wu, Neeha Zaidi, Lei Zheng, Jacquelyn W. Zimmerman, Jude M. Phillip, Elizabeth M. Jaffee, Joe W. Gray, Lisa M. Coussens, Young Hwan Chang, Laura M. Heiser, Genevieve L. Stein-O’Brien, Elana J. Fertig, Paul Macklinhttps://www.cell.com/cell/fulltext/S0092-8674(25)00750-0?rss=yeshttp://www.cell.com/cell/inpress.rssCellCell RSS feed.Wireless News CampaignJuly 26, 2025

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