title: Pathway Processor: a tool for integrating whole-genome expression results into metabolic networks.
abstract: We have developed a new tool to visualize expression data on metabolic pathways and to evaluate which metabolic pathways are most affected by transcriptional changes in whole-genome expression experiments. Using the Fisher Exact Test, the method scores biochemical pathways according to the probability that as many or more genes in a pathway would be significantly altered in a given experiment by chance alone. This method has been validated on diauxic shift experiments and reproduces well known effects of carbon source on yeast metabolism. The analysis is implemented with Pathway Analyzer, one of the tools of Pathway Processor, a new statistical package for the analysis of whole-genome expression data. Results from multiple experiments can be compared, reducing the analysis from the full set of individual genes to a limited number of pathways of interest. The pathways are visualized with OpenDX, an open-source visualization software package, and the relationship between genes in the pathways can be examined in detail using Expression Mapper, the second program of the package. This program features a graphical output displaying differences in expression on metabolic charts of the biochemical pathways to which the open reading frames are assigned.
authors.affiliation: Bauer Center for Genomics Research, Harvard University, Cambridge, Massachusetts 02138, USA.
authors.forename: Paul
authors.initials: P
authors.lastname: Grosu
authors.forename: Jeffrey P
authors.initials: JP
authors.lastname: Townsend
authors.forename: Daniel L
authors.initials: DL
authors.lastname: Hartl
authors.forename: Duccio
authors.initials: D
authors.lastname: Cavalieri
mesh_terms: D004734:Energy Metabolism / Q000235:genetics*; D020869:Gene Expression Profiling / Q000295:instrumentation / Q000379:methods / Q000706:statistics & numerical data; D015966:Gene Expression Regulation, Fungal / Q000235:genetics; D005800:Genes, Fungal / Q000235:genetics / Q000502:physiology; D016681:Genome, Fungal; D012441:Saccharomyces cerevisiae / Q000235:genetics* / Q000378:metabolism*; D012984:Software / Q000706:statistics & numerical data; D014158:Transcription, Genetic / Q000235:genetics / Q000502:physiology