Abstract: The conversion of nucleotide sequences into digital genomic signals allows using signal processing methods for the analysis of genomic data. This approach reveals surprising regularities in the distribution of nucleotides and pairs of nucleotides, in both prokaryotes and eukaryotes. These structural and statistical restrictions of genomic sequences would be difficult to identify by using only statistical and pattern matching methods, as in standard symbolic sequence analysis.

Long range regularities make the structure of a genome be less like that of a "plain text", which simply conveys a semantics in accordance to a grammar, and more like that of a "poem", which obeys additional structural rules that give "rhythm" and "rhyme". A direct application of these regularities is predicting nucleotides in a sequence, when knowing the preceding ones, in a way similar to time series prediction. This approach attempts to model processes such as DNA replication, DNA transcription, or mRNA translation, and allows to explore the possibility of low level error correction.
Moreover, genomic signal analysis (GSA) reveals the hidden ancestral structure of nucleotide sequences, before their re-structuring under the selective pressure of species separation.
GSA is also efficient in the analysis of pathogen variability. This is important for the molecular level detection of mutations that induce drug resistance, providing the clinician with information needed for a fast and accurate decision, and avoiding the lengthily and expensive phenotypic clinical studies requesting pathogen culture. The talk will present result in the molecular study of variability of Human Immunodeficiency Virus, performed in cooperation with Dr. Dan Otelea from the National Institute of Infectious Diseases “Prof.Dr.Matei Bals”, and of Mycobacterium tuberculosis, in cooperation with Dr. Dorina Banica from the National Institute of Pneumo-Phtysiology “Prof. Dr. Marius Nasta”, Bucharest, Romania and Dr. Karin Rodewald, Max-Plank – Institute of Biochemistry, Martinsried, Germany.


Brief Biography of the Speaker:
Paul Cristea graduated the Faculty of Electronics and Telecommunications (UPB - University "Politehnica" of Bucharest, Romania, 1962), the Faculty of Physics (University of Bucharest, 1969), and has a Ph.D. in Technical Physics (UPB, 1970). Since then his research and teaching activities covered an large area of Electrical Engineering and related domains including topics like Digital Signal and Image Processing, Genomic Signals, Neural and Evolutionary Systems, Computerized Medical Equipment, Evolutionary Intelligent Agents, Intelligent e-Learning Environments. He is the author or co-author of more then 130 published papers, 11 patents and contributed to more then 20 books in these fields. He is currently affiliated with UPB, the Biomedical Engineering Center (general director) and the Vrije Universiteit Brussel, Belgium, the ETRO Department. He is a corresponding member of the Romanian Academy and director of the Romanian Bioinformatics Society.