Genetics researchers are really excited about CRISPR/Cas9, an enzyme that has made it easier than ever for scientists to target a particular strand of DNA, snip part of it out, and replace it. And though its use in humans is still in its infancy, many experts predict that engineering the human genome is inevitable.
Tests on human genes are expensive and controversial, and no one is quite sure whether gene changes will have their desired effect. Now the Canadian startup Deep Genomics claims it has developed a computer program that can play out the different possible effects of genetic manipulation based on computers’ deep learning.
Understanding how genes work is complicated because they exist in a dialogue with other genes, turning each other off or on and generating different molecules for the body to use. Researchers have been trying to understand these relationships to better treat medical conditions from cancer to schizophrenia, but the web seems to be too complicated for us to understand. That’s where deep learning comes in—using a huge dataset of people’s genetic information with its various mutations, Deep Genomics’ software can learn how cells read their genetic code and what molecules they make as a result.
This information would be just as useful for precision medicine treatments as for genetic editing: “We can use our system to determine the efficacy of therapies, whether it’s a drug, or a CRISPR/Cas-9 gene editing system, whatever it is, our technology allows us to predict the effects of those modifications,” Deep Genomics founder Brendan Frey told Motherboard. “That’s a very difficult thing to do computationally; most of the approaches are experimental.”
Deep Genomics, which just launched this week, isn’t the only company using big data in the commercial genetics realm–23andMe is also developing predictive software. Deep Genomics’ program only looks at mutations that affect the process of splicing, in which new genes are inserted into DNA, which is not the only form of mutation.
So far, as the Motherboard story notes, it doesn’t look like the work conducted by Deep Genomics’ founders before its launch is any better than its competitors’. But as scientists are able to better decipher genes for treatments and the use of CRISPR becomes less controversial, genetic software, whether the Deep Genomics algorithm or others, will doubtless become important in precision medicine and beyond.