Tokyo, Japan – Scientists from Tokyo Metropolitan University have used machine learning to automate the identification of defects in sister chromatid cohesion. They trained a convolutional neural ...

Scientists from Tokyo Metropolitan University have used machine learning to automate the identification of defects in sister chromatid cohesion. They trained a convolutional neural network (CNN) with ...

Researchers from Tokyo Metropolitan University have developed a suite of algorithms to automate the counting of sister chromatid exchanges (SCE) in chromosomes under the microscope. Conventional ...

How do the chromosomal DNA molecules that encode the genome, that measure almost two meters, fit into cells that are a fraction of the size? The answer lies in the spatial organization of chromosomal ...

System schematic for automatic detection of sister chromatid exchanges. Machine learning techniques have been used to develop a set of algorithms that can identify and count SCEs in microscopy images.