^July August – 2010

Document image analysis (DIA) refers to the process of converting a raster image of a document page (a matrix of pixels) to a symbolic form consisting of textual (characters, digits, punctuation, words) and graphical (lines, geometric shapes, etc.) objects. Document descriptions in terms of these higher-level objects are significantly more compact than their image counterparts. More importantly, the rich semantic content of such descriptions makes it possible to manipulate these documents to serve a variety of uses such as searching them for specific patterns or classifying and combining them according to some criteria. Most DIA systems consist of, Binarization, Page analysis and segmentation, Preprocessing, Feature extraction, Classification, and Post processing. This talk will include a summery of some results we had, including page layout segmentation, key word searching & spotting and script recognition.

The DNA in eukaryotic cells is packed into the chromatin that is composed of nucleosomes. High resolution mapping of the nucleosome core particles on the sequence is a problem of great interest because of the role nucleosomes play in different cellular processes. Nucleosome positioning is determined by multiple factors, including the action of chromatin remodelers, competition with site specific DNA-binding proteins and DNA sequence preferences of the nucleosomes themselves. More than 30 years ago scientists started to investigate the role of the sequence in nucleosome positioning. It has emerged since then that there are intrinsic signals in the DNA sequence, such as 10.4 bp periodicity, correlated with the nucleosome formation, but the question is still not fully answered. We have designed universal high resolution nucleosome mapping probe using nucleosome DNA bendability pattern extracted from large nucleosome DNA database of C. elegans. The probe can be used to predict nucleosome affinity to any DNA sequence of interest. Our implementation of high resolution nucleosome mapping algorithm is freely available for the scientific community via our FineStr web-server.