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| Alexander Kel, Biobase GmbH |
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Alexander Kel received his Ph.D. in Bioinformatics, Molecular biology and Genetics in 1990. He studied biology and mathematics at Novosibirsk State University and obtained his M.S. in biology with special focus on mathematical biology in 1985. He worked for 15 years at the Institute of Cytology and Genetics, Russia (ICG) holding positions as a programmer, scientist, senior scientist and Vice-Head of the Laboratory of Theoretical Molecular Genetics. In 1995 he won the Academition Belaev Award. In 1999 he received an independent funding from the Volkswagen foundation and organized a Bioinformatics group at ICG. Since 2000, he has been the Senior Vice President Research & Development, BIOBASE Corporation, Wolfenbüttel-Germany and Beverly-USA.
The scientific career of Dr. Kel includes numerous research stays in the USA (e.g. 1993: Supercomputer Center, Tallahassee; 1997: University of Pennsylvania, Philadelphia; 1999, 2000: Cold Spring Harbor, NY), in Italy (1991, 1992: ITBA, Milan), and in Germany (1994, 1995, 1996, 1997-1998: GBF; 1997: MPI of Molecular Biology, Berlin).
The research experience of Dr. Kel in Bioinformatics totals more then 20 years. During his career Dr. Kel has worked in almost all branches of current Bioinformatics including: theoretical models of molecular genetic information systems, sequence analysis, gene recognition, promoter analysis and prediction, analysis of protein secondary structure, prediction of RNA secondary structure, theory of mutation and recombination process, molecular evolution, databases and gene expression studies.
Dr. Kel is the author of more then 80 scientific publications. He is also an author of several chapters in books on bioinformatics, tutorials and education materials.
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Upstream analysis of gene expression data: Reasoning microarray experiments
Alexander Kel, BIOBASE GmbH, Halchtersche Str. 33, D-38304 Wolfenbüttel, Germany
High throughput gene expression analyses, e.g with microarrays, may provide rich and valuable resources of information about genes that have a functional impact on certain disease phenotypes. Such genes are the most promising molecular targets for pharmacological intervention. The amount of data obtained however, precludes manual evaluation, though it is still the most frequent attempt to identify key genes / molecules of a certain cellular process to inspect long lists of gene names for those that fit the expertise of the researcher.
To provide explanatory models for the accumulated observations, we have elaborated an integrated strategy of "upstream analysis" which includes (i) systematic retrieval and analysis of the promoter regions of the affected genes, (ii) derivation of promoter model(s) as specific combinations of transcription factors for the co-regulated genes or subsets of them, (iii) modeling of the signaling pathways upstream of the transcription factors that were predicted as potential regulators of analyzed genes, (iv) identification of key molecules in the reconstructed pathways, (v) identification of additional candidate genes by scanning the whole human genome with the promoter model(s)obtained, (vi) a plausibility check by mapping the products of the candidate genes to the networks and comparison with the predicted one(s) from step (iii).
The tools that are systematically employed for this are the databases TRANSFAC™ (on transcription regulation) and TRANSPATH™ (on signal transduction), the sequence analysis programs MATCH™ and TRANSPLORER for the prediction of transcription factor binding sites, CMFinder (based on genetic algorithm) to identify potential composite modules, as well as the programs PathwayBuilder™ and ArrayAnalyzer™ for the reconstruction of pathways.
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