It’s very interesting to watch the emergence of Astronomy as an increasingly data-intensive endeavour requiring new approaches to knowledge integration, data analysis, data mining, and visualization. Although, as Kirk Borne of George Mason University rightly points out, astronomers are inherently trained as data-miners because they seek to characterize the known, assign the new, and discover the unknown (Borne, 2009). But what is rapidly changing is the degree to which such data-centric activities are becoming the foundation for astronomical research due in large part to the increasingly wide-spread emphasis on surveys and data integration capabilities made possible via initiatives such as the virtual observatory.
From Becciani et al. (2010). VisIVO – Integrated Tools and Services for Large-Scale Astrophysical Visualization.
Bioinformatics and the new “Astroinformatics” both require the analysis of large high-dimensional data sets. And it is important, I think, for practitioners in both fields to pay close attention to developments in database technologies, data mining algorithms, and visualization tools being developed in both scientific disciplines. For example, VisIVO is a maturing tool for visualization of high-dimensional data sets which, while designed with the astrophysics community in mind, probably has applicability for biological data sets as well. For example, could one visualize multiple properties of compounds showing activity against particular gene targets using datasets available from PubChem? In the aforementioned paper by Dr. Borne, AstroDAS, a system for supporting collaborative tagging and annotation of objects contained in astronomical catalogues is compared to (and clearly inspired by) BioDAS for the bioinformatics domain. I’d be interested in hearing about other examples of cross-talk amongst the tools and technologies designed with astronomy in mind but applied to biology and vice versa.
Posted by John Rachlin 
