Researchers use algorithm to pinpoint disease risk mutations in noncoding DNA

Deep learning algorithm used to pinpoint potential disease-causing variants in non-coding regions of the human genome

Researchers have successfully employed an algorithm to identify potential mutations which increase disease risk in the noncoding regions our DNA, which make up the vast majority of the human genome. The findings could serve as the basis for detecting disease-associated variants in a range of common diseases.

Researchers use algorithm to pinpoint disease risk mutations in noncoding DNA

Researchers from Children's Hospital of Philadelphia (CHOP) and the Perelman School of Medicine at the University of Pennsylvania (Penn Medicine) have successfully employed an algorithm to identify potential mutations which increase disease risk in the noncoding regions our DNA, which make up the vast majority of the human genome.

Algorithm pinpoints potential disease-causing variants in non-coding regions of human genome

Researchers from Children's Hospital of Philadelphia (CHOP) and the Perelman School of Medicine at the University of Pennsylvania (Penn Medicine) have successfully employed an algorithm to identify potential mutations which increase disease risk in the noncoding regions of our DNA, which make up the vast majority of the human genome.

CHOP, Penn Medicine Researchers Use Deep Learning Algorithm to Pinpoint Potential Disease-Causing Variants in Non-Coding Regions of the Human Genome

Researchers have successfully employed an algorithm to identify potential mutations which increase disease risk in the noncoding regions our DNA, which make up the vast majority of the human genome. The findings could serve as the basis for detecting disease-associated variants in a range of common diseases.