McGill University researchers have developed an artificial intelligence tool that can detect previously invisible disease markers inside single cells.<\/p>\n
In a study published in\u00a0Nature Communications, the researchers demonstrate how the tool, called DOLPHIN, could one day be used by doctors to catch diseases earlier and guide treatment options.<\/p>\n
“This tool has the potential to help doctors match patients with the therapies most likely to work for them, reducing trial-and-error in treatment,” said senior author\u00a0Jun Ding, assistant professor in McGill’s Department of Medicine and a junior scientist at the Research Institute of the McGill University Health Centre.<\/p>\n
Zooming in on genetic building blocks<\/p>\n
Disease markers are often subtle changes in RNA expression that can indicate when a disease is present, how severe it may become or how it might respond to treatment.<\/p>\n
Conventional gene-level methods of analysis collapse these markers into a single count per gene, masking critical variation and capturing only the tip of the iceberg, said the researchers.<\/p>\n
Now, advances in artificial intelligence have made it possible to capture the fine-grained complexity of single-cell data. DOLPHIN moves beyond gene-level, zooming in to see how genes are spliced together from smaller pieces called exons to provide a clearer view of cell states.<\/p>\n
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Genes are not just one block, they’re like Lego sets made of many smaller pieces. By looking at how those pieces are connected, our tool reveals important disease markers that have long been overlooked.”<\/p>\n
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Kailu Song, first author,\u00a0PhD student in McGill’s Quantitative Life Sciences program<\/p>\n
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