[UCI-Calit2] Calit2 Distinguished Lecture

[Anna Lynn Spitzer]

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Distinguished Lecture

Sponsored by Calit2

In cooperation with the Institute for Genomics and Bioinformatics and
the Center for Machine Learning and Intelligent Systems
<http://cml.ics.uci.edu/> 

Please note the change in the originally announced date.

 

Title:                                       Hidden Features of
Nucleotide Sequences Revealed by Genomic Signal Representation and
Processing 

Speaker:                                 Paul Cristea, University
"Politehnica" of Bucharest, Biomedical Engineering Center and the Vrije
Universiteit Brussel, Belgium 

Time:                                      11 a.m.

Date:                                       Friday, Jan. 18, 2008 

Location:                                Calit2 Building, Room 3008 

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 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 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,
avoiding the lengthy and expensive phenotypic clinical studies
requesting pathogen culture. 

 Bio:                             Paul Cristea received degrees from the
University "Politehnica" of Bucharest, Romania in1962, and the
University of Bucharest in 1969 before earning a Ph.D. in technical
physics from the University "Politehnica" of Bucharest (UPB) in 1970.
Since then, his research and teaching activities have covered a variety
of topics, including digital signal and image processing, genomic
signals, neural and evolutionary systems, computerized medical
equipment, evolutionary intelligent agents and intelligent e-learning
environments. He has 11 patents, is the author or co-author of more than
130 published papers and has contributed to more than 20 books. Cristea
is a professor at PUB. He is also currently affiliated with the UPB's
Biomedical Engineering Center (General Director) and the Vrije
Universiteit Brussel, Belgium. He is a corresponding member of the
Romanian Academy of Sciences and director of the Romanian Bioinformatics
Society. 

 

Faculty Sponsor: Prof.Rui J. P. de Figueiredo

                             EECS and Math Departments

 (To arrange for a meeting with the speaker, please send email to
rui at uci.edu <mailto:rui at uci.edu> ) 

 

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