Princeton researchers created a data science tool that discerns fine-tuned distinctions between gene activity associated with specific diseases and tissues. In a demonstration of the tool’s power, the team discovered four genes associated with a rare pediatric cancer. The image on the left shows a normal cell while the one on the right highlights one of the discovered genes in neuroblastoma, which afflicts babies and young children.
Images courtesy of the researchers
Data science tool that reveals molecular causes of disease shows power in infant cancer analysis
Steven Schultz, Office of Engineering Communications, Feb. 28, 2019 1:19 p.m.
Princeton University researchers are gaining new insights into the causes and characteristics of diseases by harnessing machine learning to analyze molecular patterns across hundreds of diseases simultaneously. Demonstrating a new tool now available to researchers worldwide, the team of computer scientists and biologists has already uncovered and experimentally confirmed previously unknown contributions of four genes to a rare form of cancer that primarily affects babies and young children.
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