Artificial intelligence could revolutionise glycomics datasets

Researchers have created a tool that allows glycomics datasets to be analysed using artificial intelligence for early cancer diagnoses. A team at the University of California (UC) San Diego, US, have developed a tool called GlyCompare that enables researchers to analyse glycomics datasets using artificial intelligence (AI), potentially leading to early cancer diagnoses. GlyCompare takes a systems-level perspective that accounts for shared biosynthetic pathways of glycans within and across samples. According to the team, one of the keys to the GlyCompare approach is that it looks at the biological steps needed to synthesise the subunits that make up glycans, rather than only looking at only the whole glycans themselves, thereby improving the accuracy of statistical analyses of glycomics data. To introduce their technology, the team demonstrated their ability to enhance comparisons of glycomics datasets by focusing on the hidden relationships between glycans in several contexts, including gastric cancer tissues.