Executable Cell Biology
Are living processes logical and predictable? Can we develop biological models to more fully understand the complexities of biological systems?
Yes, says Jasmin Fisher, Ph.D., researcher, executable biology, Microsoft Research Cambridge. “Over the past decade, we have generated and accumulated so much data that it exceeds the human capacity to analyze it. Data from microarrays, genome sequencing, and other large-scale technologies requires sophisticated analysis by computational methods.”
According to Dr. Fisher, “Executable cell biology is a concept gaining momentum that suggests we can develop techniques for creating dynamic models that capture time- and space-dependent processes and can automate reasoning and analysis. Such large-scale models, based on formal methods from engineering and computer science, could revolutionize biology and medicine and enable the design of new therapies.”
Dr. Fisher’s group is studying how cells make decisions, with a particular focus on the process where stem cells commit to a single lineage (leading to a single-cell type) while having the ability to undergo multilineage differentiation.
“The elucidation of intricate mechanisms that govern stem cell decisions is essential for understanding normal development. Moreover, defects in these mechanisms play an important role in diseases such as cancer.”
“We first generate a detailed map of different interactions that increase or inhibit different cellular processes. We then add dynamicity by inducing from these interactions ‘state transitions’—when a specific signal or a gene gets turned on or off. This allows us to test the translated program to determine if it correlates with cell behavior. This also can allow us to capture dynamically such processes and find out what happens first, second, etc., and how feedback comes into play.”
For example, Dr. Fisher and colleagues adapted software originally designed to find errors in microcircuitry, only they used it to study C. elegans. They found a similar warning in a simulation of signaling pathways in the worm. They predicted and later experimentally verified the existence of a specific mutation that produced a functional defect in cell growth.
“One of the ultimate goals of executable biology is to simplify model building so that any scientist can use it. My personal vision is that within five years this will become a mainstream technique in biology.”