User:Mikhail Dozmorov
Dr. Dozmorov is currently a Research Assistant Member at the Oklahoma Medical Research Foundation in the department of Arthritis and Clinical Immunology. He earned a Master of Science degree in Physics and Chemistry from Moscow Institute of Electronic Technology (Techincal University), Russia in 1997, followed by a Ph.D in Medical Biophysics from the Gothenburg University, Sweden, in 2005. He has over 8 years of extensive interdisciplinary research experience in the areas of Computational Biology and Bioinformatics, Cancer, Immunology, and Neurobiology. Dr. Dozmorov served as an Associate Editor of the MCBIOS conference proceedings, and a statistical advisor for PLoS One journal. He has published over 25 peer reviewed papers, 2 editorials, and a book chapter.
Prior joining OMRF in 2010, Dr. Dozmorov worked in a field of cancer biology applying his integrative method of computational data analysis in order to understand mechanisms of tumor cells dormancy driven by extracellular matrix. His interest in complex diseases led him to the Department of Arthritis and Clinical Immunology. He continues to develop his bioinformatics approaches to understand multi-factorial diseases by incorporating functional genomics, epigenomics, gene expression and next-generation sequencing data into an integrated model of regulatory changes behind a phenotype. One of the most important achievements was developing a system for automating genome exploration by statistical analysis of epigenomic data from the ENCODE project, called GenomeRunner http://www.genomerunner.org.
Dr. Dozmorov had initiated and led numerous collaborative projects with basic lab, clinical, and computational components. His interdisciplinary work was recognized by travel awards, best oral presentation awards, and best paper awards. His extensive research interests encompass human genome architecture and epigenomic regulation in order to define and correct patient-specific genomic and epigenomic abnormalities leading to autoimmunity. It is hoped these discoveries may ultimately lead to novel treatments and better management of complex diseases.
