title: Discovering transcriptional modules from motif, chip-chip and microarray data.
abstract: We present a method for inference of transcriptional modules from heterogeneous data sources. It allows identifying the responsible set of regulators in combination with their corresponding DNA recognition sites (motifs) and target genes. Our approach distinguishes itself from previous work in literature because it fully exploits the knowledge of three independently acquired data sources: ChIP-chip data; motif information as obtained by phylogenetic shadowing; and gene expression profiles obtained using microarray experiments. Moreover, these three data sources are dealt with in a new and fully integrated manner. By avoiding approaches that take the different data sources into account sequentially or iteratively, the transparency of the method and the interpretability of the results are ensured. Using our method on biological data demonstrated the biological relevance of the inference.
authors.affiliation: KULeuven, ESAT-SCD, Kasteelpark Arenberg 10, 3001 Leuven, Belgium.
authors.forename: Tijl
authors.initials: T
authors.lastname: De Bie
authors.forename: Pieter
authors.initials: P
authors.lastname: Monsieurs
authors.forename: Kristof
authors.initials: K
authors.lastname: Engelen
authors.forename: Bart
authors.initials: B
authors.lastname: De Moor
authors.forename: Nello
authors.initials: N
authors.lastname: Cristianini
authors.forename: Kathleen
authors.initials: K
authors.lastname: Marchal
mesh_terms: D000465:Algorithms; D002453:Cell Cycle / Q000235:genetics; D005656:Fungal Proteins / Q000235:genetics; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis; D015203:Reproducibility of Results; D012270:Ribosomes / Q000235:genetics; D012441:Saccharomyces cerevisiae / Q000166:cytology / Q000235:genetics*; D014158:Transcription, Genetic
chemical_list: D005656:Fungal Proteins