Integrative Systems Biology Visualization with MAYDAY

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doi doi:10.2390/biecoll-jib-2010-115
submission February 16, 2010
published March 25, 2010
NCBI PubMed PubMed ID 20375461

Stephan Symons, Christian Zipplies, Florian Battke and Kay Nieselt

Correspondence should be addressed to:
Stephan Symons
Center for Bioinformatics Tübingen, University of Tübingen, Sand 14, 72076 Tübingen, Germany


Visualization is pivotal for gaining insight in systems biology data. As the size and complexity of datasets and supplemental information increases, an efficient, integrated framework for general and specialized views is necessary. MAYDAY is an application for analysis and visualization of general ‘omics’ data. It follows a trifold approach for data visualization, consisting of flexible data preprocessing, highly customizable data perspective plots for general purpose visualization and systems based plots. Here, we introduce two new systems biology visualization tools for MAYDAY. Efficiently implemented genomic viewers allow the display of variables associated with genomic locations. Multiple variables can be viewed using our new track-based ChromeTracks tool. A functional perspective is provided by visualizing metabolic pathways either in KEGG or BioPax format. Multiple options of displaying pathway components are available, including Systems Biology Graphical Notation (SBGN) glyphs. Furthermore, pathways can be viewed together with gene expression data either as heatmaps or profiles. We apply our tools to two ‘omics’ datasets of Pseudomonas aeruginosa. The general analysis and visualization tools of MAYDAY as well as our ChromeTracks viewer are applied to a transcriptome dataset. We furthermore integrate this dataset with a metabolome dataset and compare the activity of amino acid degradation pathways between these two datasets, by visually enhancing the pathway diagrams produced by MAYDAY.


Stephan Symons, Christian Zipplies, Florian Battke and Kay Nieselt. Integrative Systems Biology Visualization with MAYDAY. Journal of Integrative Bioinformatics, 7(3):115, 2010. Online Journal:
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