‘Virtual cells’ aim to turn raw data into predictive models of biology

As every gamer knows, computers can plausibly simulate just about anything from the routine concerns of a household to the crises confronting a multiplanetary civilization. Simulating the fundamental unit of life — the cell — should be a walk in the park. But it’s not. Each cell is a complex ecosystem of biomolecules that interact with one another and react to external cues in ways that remain poorly understood. And what’s true of one cell type isn’t necessarily true of another. But there is an order to the chaos. ‘Virtual cell’ captures the most-basic process of life: bacterial division “The cell is a complex system, and a highly robust and resilient system,” says Emma Lundberg, a bioengineer at Stanford University in California. “But it’s also a highly structured system — the cell has an architecture.” Over the past few years, researchers have begun reverse-engineering that architecture to convert vast repositories of molecular data into ‘virtual cells’ — models that simulate the internal environment of cells both at rest and when responding to external triggers. Several teams are now tapping into deep reservoirs of transcriptomic (gene expression) and other data sets to build models that could reveal the underlying biological bases of disease and possible angles for therapeutic intervention. …