UW-Milwaukee researcher Andrew Cohen has successfully developed a software program that facilitates predicting the evolution of stem cells. The program essentially speeds up what has been a tedious process for researchers in the past.
The program was published last week in the journal Nature Methods. It applies algorithmic information theory to the growth and movement of stem cells tracked over time to show what type of cells (i.e. brain, skin, etc.) they will eventually develop into.
“People look at images and take measurements by hand,” Cohen explained. “It takes a long time, and using computers makes the process a lot less tedious.”
Stem cells all start out the same before they develop into the different cells of our bodies. Scientists do not know what triggers the stem cell’s future growth pattern into a particular type of cell, but researchers like Cohen are figuring out how to predict the cell’s future based on measurements and math.
Determining the fate of stem cells at the beginning of their growth could help scientists apply stem cells exactly where they’re needed in the body.
According to Cohen, “Neurobiologists have realized that — in all the neurodegenerative diseases, such as Alzheimer’s, Parkinson’s and Huntington’s — cell organelles transport deficiencies and are a causative effect in diseases. But how do you measure that? From an engineering perspective, it’s an exceedingly hard tracking problem.” In other words, how does one track deficiencies in cell organelles?
This is one problem that Cohen’s software helps solve.
The program does what earlier researchers were doing manually. The method applied before Cohen’s program was a tedious, time-consuming process; think of it as drawing a flipbook in a notebook vs. using animation software.
Cohen’s software takes measurements of the images of stem cells as they grow.
“We’re starting, in a bunch of different ways, to outperform the human eye,” Cohen said.
Cohen is a computer engineer, but his cross-disciplinary work is bringing progress to the fields of biology and medical research.
Cohen plans to apply the software to research in cancer biology, with a child cancer researcher looking at causes of retinal blastoma.
“With this program we hope to look for behavior differences among populations of cells that have different cancer-related cells activated or not activated,” Cohen said. “The cross-disciplinary nature of this is what makes it really interesting.”