REDUCE is an acronym that stands for Regulatory Element Detection Using Correlation with Expression, not coincidentally also the title of our paper. Based on a simple model for transcriptional regulation by independently acting transcription factors, REDUCE makes it possible to find regulatory elements based on a single microarray experiment. There is no need to first cluster genes on the basis of their expression profiles over multiple experiments, and there are no parameters to be tuned. Although the underlying model for transcriptional activation represents a gross simplification of the molecular details, our work can be seen as a first attempt to "reduce" the complexity of the genome-wide expression pattern by understanding it in terms of a relatively small number of parameters, representing the combined transcription factor activities or "regulome".

To validate our method, we have analyzed the publicly available microarray data obtained by the Brown Lab at Stanford University for diauxic shift, cell cycle, and sporulation data.

Click here to browse the results