The proposed research has three closely related objectives. The first is to develop and study different models that describe the regulatory interaction between genes. The second objective is to develop fast algorithms based on these models for detecting regulatory interactions between the genes inferred from the expression array data, i.e. for reverse engineering of the network architecture from the activity profiles of genes in the system. This includes the development of parallel computational methods for analyzing gene sequences at a much higher speed than the sequential methods. Inference about the causal relationships among genes should generate hypotheses for further experiments. The third objective is to use these methods to study the global signal circuitry of different organisms and cell types and to explain how specific generic lesions serve to reprogram the wiring diagram of cellular signaling pathways in each of the constituent cell types so as to manifest cancer and other diseases.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Mentored Quantitative Research Career Development Award (K25)
Project #
1K25HG002411-01
Application #
6415606
Study Section
Ethical, Legal, Social Implications Review Committee (GNOM)
Program Officer
Graham, Bettie
Project Start
2001-12-17
Project End
2006-11-30
Budget Start
2001-12-17
Budget End
2002-11-30
Support Year
1
Fiscal Year
2002
Total Cost
$111,796
Indirect Cost
Name
University of California Los Angeles
Department
Biostatistics & Other Math Sci
Type
Schools of Arts and Sciences
DUNS #
119132785
City
Los Angeles
State
CA
Country
United States
Zip Code
90095