NVIDIA and Harvard researchers use AI to make genome analysis faster and cheaper!

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This breakthrough could lead to identifying biomarkers for diseases, via engadget

Scientists from NVIDIA and Harvard have made a huge breakthrough in genetic research. They developed a deep-learning toolkit that is able to significantly cut down the time and cost needed to run rare and single-cell experiments. According to a study published in Nature Communications, the AtacWorks toolkit can run inference on a whole genome, a process that normally takes a little over two days, in just half an hour. It’s able to do so thanks to NVIDIA’s Tensor Core GPUs.

AtacWorks works with ATAC-seq, a well-established method designed to find open areas in the genome of healthy and diseased cells. These “open areas” are subsections of a person’s DNA that are used to determine and activate specific functions (think liver, blood or skin cells). This is the part of a person’s genome that could give scientists indications on whether a person could have Alzheimer’s, heart disease or cancer.

ATAC-sec usually requires the analysis of tens of thousands of cells, but AtacWorks is able to get the same results using only tens of cells. Researchers also applied AtacWorks to a dataset of stem cells that produce red and white blood cells, subtypes that typically can’t be studied using traditional methods.

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