Developed at the Institute for Data Analysis and Visualization (IDAV)
, in collaboration with the
, PointCloudXplore is an advanced visualization tool
for spatial and temporal 3D gene expression data. It was developed to help biologists understand the relationship between gene expression patterns in three dimensions.
To support analysis of these high dimensional data sets, PointCloudXplore integrates multiple views to ease analysis of complex gene expression data. Each view emphasizes
different data properties, and interaction between the views makes it possible to perform detailed analyses of the presented data. This type of interaction blends high-dimensional information exploration with interactive, 3D visualization.
Available at: http://bdtnp.lbl.gov/Fly-Net/bioimaging.jsp?w=pcx
User manual http://bdtnp.lbl.gov/Fly-Net/pcx.jsp?w=vis
PointCloudXplore was part of my Master and Ph.D. research. The project is currently inactive.
Software Architect and Developer
Oliver Rübel, Gunther H. Weber, Soile V.E. Keränen, Charless C. Fowlkes, Cris Luengo Hendriks, Lisa Simirenko, N.Y. Shah, Michael B. Eisen, Mark D. Biggin, Hans Hagen, J. Damir Sudar, Jitendra Malik, David W. Knowles, and Bernd Hamann, "PointCloudXplore: Visual analysis of 3D gene expression data using physical views and parallel coordinates", in: Sousa Santos, B., Ertl, T. and Joy, K.I., eds., Data Visualization 2006 (Proceedings of EuroVis 2006), Eurographics Association, Aire-la-Ville, Switzerland, pp. 203-210