Communications of the ACM
Computer Scientists Model Cell Division
Using a computational model, researchers can infer properties about how cells divide by studying regular patterns like hexagons in epithelial tissues.
Courtesy of Radhika Nagpal, Harvard SEAS
Harvard University computer scientists have developed a model for studying the arrangement of tissue networks that are created by cell division. "We developed a model that allows us to study the topologies of tissues, or how cells connect to each other, and understand how that connectivity network is created through generations of cell division," says Harvard professor Radhika Nagpal. "Given a cell division strategy, even if cells divide at random, very predictable 'signature' features emerge at the tissue level." The new framework could create new insights on how multicellular systems achieve, or fail to achieve, robustness from the seemingly random behavior in groups of cells, and help researchers looking to artificially emulate complex biological behavior.
Using the computational model, Nagpal and her colleagues demonstrated that the regularity of the tissue can act as an indicator for inferring properties about the cell division mechanism itself. "Even with modern imaging methods, we can rarely directly 'ask' the cell how it decided upon which way to divide," Nagpal says. "The computational tool allows us to generate and eliminate hypotheses about cell division."
The researchers plan to use the new model to detect and study mutations that adversely affect cell division processes in epithelial tissues, which can cause cancer. "One day we may even be able to use our model to help researchers understand other kinds of natural cellular networks, from tissues to geological crack formations, and, by taking inspiration from biology, design more robust computer networks," Nagpal says.
From Harvard University
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