Ph.D. Qualifying Project -- February, 2002

Extensions to REDUCE: Regulatory Element Detection Using Correlation With Expression

AUTHORS: Daniel Grossman and Walter L. Ruzzo (Faculty Advisor)
Abstract

We present extensions to a recently proposed computational method for discovery of transcription factor binding motifs by correlating genome sequence and genome-wide expression data. We have augmented the original approach by making feasible the examination of a far larger search space and by incorporating an empirical background distribution based on negative controls. Analyses of datasets used by the proponents of the original model and of other publicly available sets confirm our algorithm's aptitude for uncovering motifs known in the biological literature as well as novel putative regulatory sequences.

Keywords:
Microarray Expression Data, Motif-Finding, Regulatory Element Detection, Sequence Analysis

Please download our paper here: Extensions to REDUCE

References

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This page last updated: Friday, March 8, 2002.
E-mail the authors: Daniel Grossman, Larry Ruzzo