Abstract
New high-resolution approaches for mapping ultrastructure of cells in 3D are leading to unprecedented quantities of spatial data. Here we present Illoura, a software tool for the integrated management, analysis and visualization of these data within a semantic context, and illustrate its capability by analysis of spatial relationships in mammalian beta cells. http://www.visiblecell.com/illoura. Supplementary data are available at Bioinformatics online.
Highlights
One of the most important challenges facing modern bioinformatics is the reconstruction and analysis of biomolecular interaction networks in cells
Availability: http://www.visiblecell.com/illoura Contact: m.ragan@uq.edu.au Supplementary information: Supplementary data are available at Bioinformatics online
Described here in reference to biomolecular and cellstructural data, Illoura broadly supports the organization and integrated analysis of scientific data presented in Resource Description Framework (RDF) (Manola and Miller, 2004)
Summary
One of the most important challenges facing modern bioinformatics is the reconstruction and analysis of biomolecular interaction networks in cells These networks are often represented as graphs in which the vertices represent biomolecules (e.g. proteins) and the edges depict functional relationships (catalysis, signaling). Localization contributes to the emergence of function, e.g. by bringing together or separating different sets of biomolecules and differentially facilitating or constraining different interaction subgraphs These structures, in turn, are often arrayed within the cell in characteristic, spatially complex ways that bear strong quantitative implications for the parameterization of dynamic models, e.g. of transport or diffusion. Relationships can often be calculated quickly when and if needed, and made available for inference We describe such a strategy and present a Java application, which we call IllouraTM, which addresses the challenges of analysis, visualization and querying over spatial biological data. The amount of analytical work required is bounded by the question being posed rather than by the size of the model, and the output from any analysis is immediately embedded in a semantic context, and can persist as such
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