The Eclipse Rich Client Platform (RCP) is very powerfull, and takes a lot of architectural things of your hand when developing a bio- and chemoinformatics GUIs. Bioclipse is based on it. One thing the RCP offers is a Help View which works with plain (X)HTML files, and one neat feature is the context help. It is help shown in the Help View when one focused on a specific GUI element.

As an example, the below figure gives the context help for the JmolView in the Jmol plugin (bc_jmol) plugin for Bioclipse:

On the right side of the Jmol view (showing 1SPX) is the Help View, showing the context help for the Jmol View pointing to the 'Jmol Script Commands Reference'.

With chemometrics in mind (QSAR, data mining, ...), I have started working on matrix support in Bioclipse, because the matrix is the important step between (bio-)molecular content and statistical analysis. I implemented this such that the actual matrix implementation can be freely chosen, that is, bc_statistical provides a IMatrixImplementation extension point. The plugin bc_jama provides a JAMA based extension for this, but other implementations are possible, and possibly useful.

David Strumfels posted news about the Useful Chemistry CMLRSS feed. He explains how this feed can be accessed using Jmol and Bioclipse. The latter are accompanied by two AVI movies: one about creating a new OPML file, and one about accessing the CMLRSS file from the OPML.
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I started a spin-off blog earlier this week: kemistry desktop environment. It will deal with integration of chemistry on opensource desktops, with KDE as one of them. Today, it features an overview of earlier blogs on the subject in this new blog.
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This blog deals with chemblaics in the broader sense. Chemblaics (pronounced chem-bla-ics) is the science that uses computers to solve problems in chemistry, biochemistry and related fields. The big difference between chemblaics and areas such as chem(o)?informatics, chemometrics, computational chemistry, etc, is that chemblaics only uses open source software, open data, and open standards, making experimental results reproducible and validatable. And this is a big difference!
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