Dmitry Sitnikov

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We have investigated DNA segregation in E. coli by inserting multiple lac operator sequences into the chromosome near the origin of replication (oriC), in the hisC gene, a terminus marker, and into plasmids P1 and F. Expression of a GFP-LacI fusion protein allowed visualization of lac operator localization. oriC was shown to be specifically localized at or(More)
Manually annotated corpora are critical for the training and evaluation of automated methods to identify concepts in biomedical text. This paper presents the concept annotations of the Colorado Richly Annotated Full-Text (CRAFT) Corpus, a collection of 97 full-length, open-access biomedical journal articles that have been annotated both semantically and(More)
The Gene Ontology (GO) Consortium (GOC, http://www.geneontology.org) is a community-based bioinformatics resource that classifies gene product function through the use of structured, controlled vocabularies. Over the past year, the GOC has implemented several processes to increase the quantity, quality and specificity of GO annotations. First, the number of(More)
The Gene Ontology (GO) is an important component of modern biological knowledge representation with great utility for computational analysis of genomic and genetic data. The Gene Ontology Consortium (GOC) consists of a large team of contributors including curation teams from most model organism database groups as well as curation teams focused on(More)
MicroRNA regulation of developmental and cellular processes is a relatively new field of study, and the available research data have not been organized to enable its inclusion in pathway and network analysis tools. The association of gene products with terms from the Gene Ontology is an effective method to analyze functional data, but until recently there(More)
Annotations of genes and gene products in model-organism databases with Gene Ontology (GO) terms have become an important knowledge resource in biomedical research, which has spurred many efforts at automating this labor-intensive manual curatorial activity, including many text-mining approaches. In an effort to provide some guidance on these text-mining(More)
The rough set concept is a relatively new mathematical approach to vagueness and uncertainty in data. The rough set theory is a well-understood formal framework for building data mining models in the form of logic rules, on the basis of which it is possible to issue predictions that allow classifying new cases. The indiscernibility relation and(More)
The rough set concept is a relatively new mathematical approach to vagueness and uncertainty in data. The rough set theory is a well-understood formal framework for building data mining models in the form of logic rules, on the basis of which it is possible to issue predictions that allow the classification of new cases. The indiscernibility relation and(More)
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