Neural network fills in data gaps for spatial analysis of chromosomes

Computational methods used to fill in missing pixels in low-quality images or video also can help scientists provide missing information for how DNA is organized in the cell, computational biologists have shown. Filling in this missing information will make it possible to more readily study the 3D structure of chromosomes and, in particular, subcompartments that may play a crucial role in both disease formation and determining cell functions.