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Latest News

If you're using OpenDX and have some nifty pictures you'd like to share, contact us to get them added to the gallery.

  • October 14, 2007 - The CVS is again available. After being off-line at IBM for 4 months, it is now back up and an OpenSource repository. Check it out in the Developers section.
  • September 11, 2006 - The new OpenDX DVD is available for purchase from VIS, Inc.
  • September 9, 2006 - New mailing lists are up for use. Please come join us there if you prefer e-mail over user forums.
  • August 30, 2006 - OpenDX 4.4.4 is now available. Binaries for the highest demand operating systems are now available. See the ChangeLog for the list of changes.
  • March 22, 2005 - Jerry Hagon has updated his font converter script with some helpful documentation changes. Click here to download it. He also has a new dvidx which allows dvi output to be imported into OpenDX. Check out DXfontutils for more info.
  • July 1, 2004 - VIS, Inc. has updated its book, OpenDX: Paths to Visualization, to version 2 reflecting the changes in OpenDX 4.3.

User Quote

"I chose DX for both research and product development because of its fundamentally sound architecture. The combination of a well designed data model and a small set of powerful computational modules allows rapid development of programs that are both simpler and more general. In four years, its value has been proven time and again. We will continue to use DX in our radiation treatment planning systems."

Michael P. Zeleznik, Ph.D.
RAHD Oncology Products / University of Utah

Data Explorer in Action


This is a visualization of DNA microarray ("gene chip") data. Gene chips allow you to measure the expression levels of thousands of genes at once in a given tissue. A typical data set assays some number of samples (a few to a few dozen) in order to assess changes in expression between the samples. For example, one data set might compare diseased versus normal tissues, while another might compare samples from different ages or dietary regimens. (The possible variations are endless.) Identifying the few genes out of thousands whose expression is significantly different in sample A vs. sample B can provide important clues as to the underlying genetic factors that make A and B different. The particular data set in the screenshot is a survey of expression levels for about 30,000 genes in 122 samples from "your basic healthy, adult laboratory mouse". The study was done by the Genomics Institute of the Novartis Research Foundation.


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