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NVIDIA revolutionizes genome analysis. Researchers at NVIDIA and Harvard have made a huge breakthrough in genetic research.
NVIDIA is revolutionizing genome analysis
Harvard researchers are working with Nvidia researchers to identify biomarkers for diseases such as Alzheimer’s or cancer. They have developed a set of deep learning tools. It is able to significantly reduce the time and costs required to run rare and single-cell experiments.
According to a study published in Nature Communications, the AtacWorks toolkit can infer an entire genome. The process, which normally takes a little over two days, can be shortened to just half an hour. This is possible thanks to NVIDIA Tensor Core GPUs.
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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.
This is the part of a person’s genome that could give researchers indications as to whether a person might have Alzheimer’s, heart disease or cancer.
AtacWorks could help researchers discover drugs
ATAC-seq usually requires analysis of tens of thousands of cells. However, AtacWorks is able to achieve the same results using only dozens of cells. The researchers also applied AtacWorks to a set of stem cell data that produce red and white blood cells.
These subtypes usually cannot be studied using traditional methods. But with AtacWorks, they were able to identify separate parts of the DNA associated with white blood cells and red blood cells, respectively.
The ability to analyze the genome faster and cheaper will help identify specific mutations or biomarkers that could lead to certain diseases. It could even help in the discovery of drugs, helping researchers figure out how the disease works.
“With very rare cell types, it is not possible to study the differences in their DNA using existing methods.”, said NVIDIA researcher and lead author Avantika Lal. “AtacWorks can help not only reduce the cost of collecting chromatin accessibility data, but also open up new possibilities in drug discovery and diagnosis.”
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