Mapping 3D-super-enhancers with machine learning to pinpoint regulators of cell identity
Scientists usually study the molecular machinery that controls gene expression from the perspective of a linear, two-dimensional genome—even though DNA and its bound proteins function in three dimensions (3D). To better understand how key components of this machinery, such as super-enhancers, regula...
Image: Phys.org
Scientists usually study the molecular machinery that controls gene expression from the perspective of a linear, two-dimensional genome—even though DNA and its bound proteins function in three dimensions (3D). To better understand how key components of this machinery, such as super-enhancers, regulate genes in this 3D reality, scientists at St. Jude Children's Research Hospital have developed a new algorithm called BOUQUET.
Originally published at Phys.org
