PMC:1624833 / 24690-25679 JSONTXT

{"project":"2_test","denotations":[{"id":"16952321-14555958-1695224","span":{"begin":223,"end":225},"obj":"14555958"},{"id":"16952321-12399584-1695225","span":{"begin":226,"end":228},"obj":"12399584"}],"text":"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."}