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The technical advance of high-throughput techniques provides the opportunity to generate complementary transcriptomic, metabolic, and proteomic datasets that allow a detailed insight into plant systems. This huge amount of profiling data can hardly be interpreted by an individual researcher. The publicly available MapMan software tool offers scientists a combination of biological pre-knowledge, data visualization, and bioinformatics solutions, which help to access profiling data in an intuitive and purposive way, regardless of their field of expertise.

The MapMan software functionally categorizes genomic and metabolomic profiles in order to display color-coded data onto biochemical pathways or customized maps. This approach allows the user to investigate data assigned to certain biological processes or, in any desired combination, to represent individual research interests. MapMan is a generic tool that has been used to investigate responses of the model plant Arabidopsis thaliana to low sugar (induced by extension of the night period or a mutation in plastid phosphoglucomutase). The use of MapMan visualization revealed a concerted reprogramming of plant metabolism in response to sugar depletion, qualitatively similar in both treatments. Analysis of metabolism-associated pathways indicated a general switch from anabolism to catabolism, whereas global cell functions maps suggested a repression of cellular growth and function, accompanied by beginning senescence processes. The visual data analysis approach finally led to the identification of candidate low carbon-signalling components (e.g. trehalose-6-phosphate). Due to its modular structure, MapMan can be adapted to any biological organism and analytical approach. The user benefits from online technical support, updates of functional genome annotations, and corresponding maps. Current developments include the functional annotation of other plant genomes and the implementation of statistics modules that allow data pre-processing with subsequent visualization of results.

To achieve a comprehensive understanding of plant systems information from a plant genome, metabolome and proteome are necessary. The development of profiling techniques enables scientists to generate these data, but in contrast to analytical progress the biological interpretation of profiling data is still in its infancy. Although many bioinformatics tools have been developed to address problems of data integration, biologist-friendly solutions are only rarely available. MapMan was developed to design an easily accessible interface that enables efficient user-driven data visualization. MapMan allows the user to display profiling data as colored spots onto maps of choice. Placing profiling data into their biological background facilitates the analysis of responses to a specific treatment, stress, or developmental process. Therefore, the tool comes with a series of pre-defined maps that either give broad overviews on global biological processes, or allow a detailed analysis of biochemical pathways. MapMan translates profiling data into visually accessible information in order to facilitate the biological interpretation of large-scale datasets.