Machine learning is now helping researchers analyze the makeup of unfamiliar cells, which could lead to more personalized medicine in the treatment of cancer and other serious diseases.
Researchers at the University of Waterloo developed GraphNovo, a new program that provides a more accurate understanding of the peptide sequences in cells. Peptides are chains of amino acids within cells and are building blocks as important and unique as DNA or RNA.
“What scientists want to do is sequence those peptides between the normal tissue and the cancerous tissue to recognize the differences,” said Zeping Mao, a PhD candidate in the Cheriton School of Computer Science who developed GraphNovo under the guidance of Dr. Ming Li.
Read the full press release from Waterloo News to learn more.