title: Creating gene set activity profiles with time-series expression data.
abstract: The use of predefined gene sets has become crucial in the interpretation of genomewide expression data. A limitation of the existing techniques that relate gene expression levels to gene sets is that they cannot readily be applied to time-course microarray data. The ability to attach statistical significance to the behaviour of biological processes over time would greatly contribute to understanding the complex regulatory mechanisms in the cell. We propose a statistical testing procedure based on the central limit theorem to assess the enrichment of a gene set. The technique is applied on time-course microarray data to generate gene-set specific 'activity profiles'.
authors.affiliation: Department of Mediamatics, Delft University of Technology, Mekelweg 4, 2628 CD Delft, The Netherlands. t.a.knijnenburg@tudelf.nl
authors.forename: T A
authors.initials: TA
authors.lastname: Knijnenburg
authors.forename: L F A
authors.initials: LF
authors.lastname: Wessels
authors.forename: M J T
authors.initials: MJ
authors.lastname: Reinders
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D020869:Gene Expression Profiling / Q000379:methods*; D008954:Models, Biological; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D020543:Proteome / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology*
chemical_list: D020543:Proteome