A better understanding of the complex interactions required to regulate transcription in a eukaryotic cell will provide us with additional tools for characterizing gene function, new targets for drug development, and invaluable information on cellular responses to the environment. This project will use the in vivo DNA binding pattern of Rap1 in yeast, with additional data from other interacting factors (chromatin modifications and other DNA binding proteins) to construct a discriminate function to classify DNA sites as binding or non-binding. This technique will allow us to determine which variables (additional factors) are related to the criterion variables (binding vs non-binding), and secondly to predict if an unknown site should be grouped as a binding or non-binding based on the predictor variables. After determining the variables that best predict Rap1 binding, we plan to analyze other transcription factors and determine if the same predictor variables are in common for different transcription factors. From this data we can determine if a predictor variable is specific to a given protein or general to all transcription factors. This research will tease apart the different processes that influence DNA binding in vivo and provide invaluable information about how transcription is regulated.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Postdoctoral Individual National Research Service Award (F32)
Project #
5F32HG002989-02
Application #
6796375
Study Section
Special Emphasis Panel (ZRG1-F08 (20))
Program Officer
Graham, Bettie
Project Start
2003-08-04
Project End
2006-08-03
Budget Start
2004-08-04
Budget End
2005-08-03
Support Year
2
Fiscal Year
2004
Total Cost
$42,976
Indirect Cost
Name
University of North Carolina Chapel Hill
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
608195277
City
Chapel Hill
State
NC
Country
United States
Zip Code
27599
Buck, Michael J; Nobel, Andrew B; Lieb, Jason D (2005) ChIPOTle: a user-friendly tool for the analysis of ChIP-chip data. Genome Biol 6:R97