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Markus Covert: How to build a computer model of a cell

A bioengineer sets out to create a computer simulation of a single living cell and comes to grips with the remarkable complexity that is life.

3D rendering of E. coli bacteria under the microscope, partially blurred with a black background

Covert built a model of E. coli that would allow researchers to run experiments on a simulated cell on a computer. | Adobe Stock/origami88

When Stanford bioengineer Markus Covert first decided to create a computer model able to simulate the behavior of a single cell, he was held back by more than an incomplete understanding of how a cell functions, but also by a lack of computer power.

His early models would take more than 10 hours to churn through a single simulation and that was when using a supercomputer capable of billions of calculations per second.

Nevertheless, in his quest toward what had been deemed “a grand challenge of the 21st century,” Covert pressed on and eventually published a paper announcing his success in building a model of just one microbe: E. coli, a popular subject in biological research. The model would allow researchers to run experiments not on living bacteria in a lab, but on a simulated cell on a computer.

After all was said and done, however, the greatest takeaway for Covert was that a cell is a very, very complex thing. There were fits and starts and at least one transcendent conceptual leap — which Covert has dubbed “deep curation” — needed to make it all happen, but he found a way. As Covert points out, no model is perfect, but some are useful. And that is how usefulness, not perfection, became the goal of his work, as he tells fellow bioengineer Russ Altman in this episode of Stanford Engineering’s The Future of Everything podcast. Listen here, and subscribe to the podcast here.