The principle of spatial mapping is familar to microscopists. It is, for example, employed in conjunction with x-ray fluorescence spectrometry to draw up maps showing the distribution of elements in a materials surface. Although widely exploited in scanning electron microscopy, the technique of spatial mapping is rarely applied to other types of images. With the recent development of automated methods for recognizing and extracting details from digital images, however, it has become feasible to extract patterns from the transmission electron microscope image and overlay the original image with representations from the data. Pattern extraction, executed in a data mining scheme, is an area of common interest to researchers in machine discovery, data visualization, and high performance computing. Since the resolution of an electron microscopic image, if completely conserved in the conversion into digital format, can range into many millions of pixels, microscopy is one of the most promising areas for data mining applications.

This capability is particularly well-suited to investigating the problem of chromatin higher order structure. The highest order of packing that is readily seen in transmission electron micrographs of chromatin is the 30 nm fiber, the approximate size of which has been confirmed by x-ray diffraction studies.