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Stephen W. Davies Institute for Biomaterials and Biomedical Engineering and Department of Electrical and Computer Engineering
Contact the Professor at: Email:stephen.davies@utoronto.ca Phone:416-946-7176 Fax:416-978-4317 Medical Sciences Building, Room 4226, 1 King's College Circle |
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Interests:
Genetic circuits: design, analysis, implementation, applications;
Bioinformatics: DNA sequencing, hybridization arrays, DNA computing;
Signal processing: signal modeling, detection, estimation and array processing;
Communications: sequential detection, wireless systems.
Late Breaking News:
Jan 30 - Canada Foundation for Innovation awards grant for "Advanced Cellular Instrumentation Laboratory". Our renamed lab will be able to acquire a quarter million dollars worth of new instrumentation to support genetic circuit design and systems modeling of biological systems.
Research:
Our research is directed at improving the extraction of sequential molecular biological information through the application of communication theory.
Our previous work has developed a model for DNA sequencing by gel electrophoresis.The model encompasses fluctuations and distortions arising from both chemical and physical processes.It has been used to derive the first optimal DNA sequencing algorithm.More recently, an algorithm based on the same general approach has been developed for local proof reading of DNA sequencing data. Further identification of the mechanisms behind the model continues to be of interest.
Our current focus is on DNA hybridization arrays with a long-term goal of addressing real-time intracellular instrumentation.DNA computing is a complementary side interest.
Hybridization arrays allow identifying which genes are currently active in a cell. We have developed image processing software that applies maximum likelihood methods to the estimation of gene expression. We are trying to identify and quantify the error mechanisms exhibited in DNA hybridization array data.The work should have relevance to both the clinical use of hybridization arrays and the use of such arrays for DNA computing.
Hybridization arrays offer the ability to study the
time dependent expression of thousands of genes simultaneously.Many
researchers now believe that multiple genes and pathways redundantly contribute
to fulfilling the same functions.Single
pathway models are then an unrealistic means to conceptualize the activity
in the cell.Rather some summary
model that effectively captures cellular activity is needed – and hopefully
this model will have diagnostic and prescriptive value.In
the hope of finding useful analogs, we are investigating summary models
in other environments, e.g. communications networks.
Moving towards intracellular instrumentation, we have recently received funding for a project entitled "Genetic Circuit Design". Using plasmids inserted into bacteria, we are creating analogs to standard electronic circuits. Eventually, we hope to create intracellular instruments based on these circuits.
DNA computing is currently limited by the errors that accumulate through the various processing steps.Building on the earlier work of Garzon et al, we are creating models of the error process and will apply more advanced codes that depend on the structure of those models.
Representative Papers:
1)S.W. Davies, M. Eizenman, S. Pasupathy, W. Muller, G. Slater,“Models of local behavior of DNA electrophoresis peak parameters”, Electrophoresis 1999, 20 No. 7, 1443-1454.
2)S.W. Davies, M. Eizenman, S. Pasupathy,"Optimal structure for automatic processing of DNA sequences", IEEE Trans. Biomed. Eng., Vol.46, No.9, Sept. 1999, pp.1044-1056.
Ph.D. Thesis: Application
of Communication Theory to Automatic DNA Sequencing