Modeling Cooperative Gene Regulation Using Fast Orthogonal Search

Abstract

Gene regulation is a complex and relatively poorly understood process. While a number of methods have suggested means by which gene transcription is activated, there are factors at work that no model has been able to fully explain. In eukaryotes, gene regulation is quite complex, so models have primarily focused on a relatively simple species, Saccharomyces cerevisiae. Because of the inherent complexity in higher species, and even in yeast, a method of identifying transcription factor (TF) binding motifs must be efficient and thorough in its analysis. Here we propose a method using the very efficient Fast Orthogonal Search (FOS) algorithm in order to uncover motifs as well as cooperatively binding groups of motifs that can explain variations in gene expression. The algorithm is very fast, exploring a motif list and constructing a final model within seconds or a few minutes, produces model terms that are consistent with known motifs while also revealing new motifs and interactions, and causes impressive reduction in variance with relatively few model terms over the cell cycle.