Rice University bioengineer Oleg Igoshin
was awarded a $700k grant
from the National Science Foundation to fund a project that will measure cell-emergent behavior through machine-learning-based quantifications. Igoshin is the principal investigator and Ankit Patel
, a jointly appointed professor at Rice University and Baylor College of Medicine, is co-principal investigator.
“We are very excited to have an opportunity to bring recent advances in deep learning and computer vision into the systems biology field,” Igoshin said.
The aim of the research is to connect the collective behavior of cells in a simple model organism to its underlying genetic networks, establishing metrics to systematically understand the effects of genetic perturbations on self-organization dynamics. Recent advances in deep-machine learning in the field of computer vision have demonstrated the power of these approaches to quantify and classify images in a robust manner, as they are insensitive to perturbations. Therefore, machine learning has the potential to connect the quantify the effect of genetic perturbation on the collective behavior of a bacterial biofilm and thereby uncover the underlying genetic networks.
The projected completion date is 2023. The methodology developed is expected to be broadly applicable, with outreach to bring applicable resources to local AP Biology high school students.