A MapMan-based web-application that extracts gene expression level of your favourite gene from databases like AtGeneExpress and NASC, and visualises it in false-colour code on simple diagrams

Microarray experiments generate a fl ood of information that is hard to interpret in a comprehensive and systemic manner. Thus the individual scientist cannot benefi t from the potential of full genome analyses and biological messages remain uncovered. Many software tools have been developed during the last years that facilitate the scientist’s access to high-throughput datasets, but only few of them are suitable for biologists without any bioinformatic training. The MapMan tool displays large-scale datasets onto familiar pathway maps and aids to analyse profi ling experiments intuitively (Thimm et al. 2004). The new web-application provides a complementary data mining approach tracking expression data of a restricted set of favourite genes in public resources (AtGeneExpress, NASC) which are subsequently displayed as virtual in-situ hybridisations/Northern analysis onto treatment-related maps using a web-interface. For a fi rst build diurnal and developmental expression profi les of Blaesing et al. and Weigel et al. were used to reveal gene expression levels during a day/night cycle and in different organs throughout the Arabidopsis lifecycle. Normalised expression data are pre-processed using the in-house ComprehensiveSystemsBiology. DataBase (Steinhauser et al.) and transmitted to a modifi ed MapMan webapplication. Gene expression levels are automatically mapped in false-colour code onto diurnal maps and Arabidopsis diagrams of the analysed organs at defi ned states of development (Lohmann and Schmid). Additionally the user gets a graphical overview if his genes of interest were differentially expressed upon hormone, cold and other treatments. The presented web tool bundles visually the fast growing quantity of information stored in public profi ling resources and facilitates biologist’s everyday life to trace complementary information of their genes of interest and therefore aids scientists to generate biological hypothesis