PMC:1624833 / 24690-25679 JSONTXT

To demonstrate the ability of our visualization algorithm to highlight differences between biclusters in similar datasets, we analyzed datasets of transcriptional regulation in two experimental conditions in S. cerevisiae [30,31]. Each dataset is a binary matrix whose columns represent transcription factors and whose rows represent genes in S. cerevisiae. A matrix entry contains a one if a ChIP-on-chip experiment indicates that the transcription factor binds to the promoter of the gene with a p-value at most 0.001. An important problem that arises in the analysis of this data is determining if a set of genes are collectively regulated by a set of transcription factors and whether this combinatorial regulation changes when the cell is exposed to stress. Although ChIP-on-chip data is noisy and significant effort may be needed to clean it up, the analysis we present next demonstrates that a combination of biclustering and our layout algorithm yields biologically useful results.