The University of Waterloo’s GraphNovo, utilizing machine learning, significantly advances the accuracy of peptide sequencing in cells, offering breakthroughs in personalized cancer treatment and vaccine development. Credit: SciTechDaily.com
The breakthrough in AI could result in the development of highly personalized medicine for treating serious diseases.
Machine learning technology is aiding scientists in examining the composition of unknown cells, potentially leading to personalized medicine for 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 are a set of organic compounds used to build proteins. There are about 500 naturally occurring known amino acids, though only 20 appear in the genetic code. Proteins consist of one or more chains of amino acids called polypeptides. The sequence of the amino acid chain causes the polypeptide to fold into a shape that is biologically active. The amino acid sequences of proteins are encoded in the genes. Nine proteinogenic amino acids are called “essential” for humans because they cannot be produced from other compounds by the human body and so must be taken in as food.
” data-gt-translate-attributes='[{“attribute”:”data-cmtooltip”, “format”:”html”}]’ tabindex=”0″ role=”link”>amino acids within cells and are building blocks as important and unique as
“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 Ph.D. candidate in the Cheriton School of Computer Science who developed GraphNovo under the guidance of Dr. Ming Li.
This sequencing process is particularly difficult for novel illnesses or cancer cells, which may not have been analyzed before. While scientists can draw on an existing peptide database when analyzing diseases or organisms that have previously been studied, each person’s cancer and immune system are unique.
To quickly build a profile of the peptides in an unfamiliar cell, scientists have been using a method called de novo peptide sequencing, which uses mass spectrometry to rapidly analyze a new sample. This process may leave some peptides incomplete or entirely missing from the sequence.
