Computer model enables better understanding of what happens during and after stroke

The work was featured in the journal PLOS Computational Biology.

The ability to examine strokes and other biological processes, through the use of computer simulations rather than after the fact on actual organisms, may significantly accelerate how quickly discoveries can be made in fighting diseases. The ability to model and simulate different treatments prior to administering them to a patient can help predict with more certainty which therapeutic approaches may be the most effective.

"This is the first step in being able to suggest {to health care providers} that if you do X and Y, you'd get a much bigger effect than what you're currently doing," said Dr. Jason McDermott, a PNNL computational biologist and lead author on the paper.

The team developed novel mathematical approaches for extending existing methods of determining causal relationships between genes that are driving biological processes. They implemented ordinary differential equations—a process for describing how things change over time—to improve their ability to infer what these gene relationships might look like and to allow more dynamic simulation of these biological processes over time.

The team is looking at improving the model to simulate events that are happening during a biological process for which there isn't pre-existing data. Additionally, they plan to test the effect of adding drugs to a treatment plan and also will be looking at micro RNA molecules that currently aren't included in the model.

More information: McDermott, J. et al., Modeling Dynamic Regulatory Processes in Stroke, PLoS Computational Biology 8(10): e1002722. DOI:10.1371/journal.pcbi.1002722

Journal reference: PLoS Computational Biology

Provided by Pacific Northwest National Laboratory