For some time I have been stealing an hour here and there for the rrdf package for R. This package is based on Apache Jena and allows reading and writing of RDF triples, as well as doing local and remote SPARQL querying. BTW, rrdf is not only R package to provide SPARQL functionality, and another package will be demoed at SWAT4LS.

It took me some time to get around to it, but I finally set up a vignette with Sweave for this package, but here it is, explaining some basic functionality of the package, just in time for #swat4ls:

So, with a week or so, I used <iframe> in the blog a few times now. The above one is being served by Google Drive.
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The past few months has seen an increasing paper trail for our Open PHACTS projects. Lot's of cool stuff is ongoing, and more and more is getting openly available. There is a steep learning curve within the project on being Open, and the project makes sure it is done properly. But it takes time. With the Open Standards and Open Source getting out now, I think we have a reasonable start.

One day on, and still struggling with the chemistry behind gene regulation. Let no biologist ever tell me again not to use acronyms (yes, I am looking at you!). But it is interesting. I learned a lot about ChIP, histone modifications, etc, etc. This is an amazing world, where specific histone complex protein residues get methylated, acetylated, citrullinated, and phosphorylated.

I have started learning about epigenetics, and particularly the regulatory effects of DNA methylation and histone acetylation. It's cool, it's hot, it's everything we hope will explain genetics, because genes certainly did not.

The chemistry behind this involves interesting pathways, involves storage of information that passes from one generation to another... epigenetic effects down to the grandchild generation have repeatedly been shown now.

At some point I had thought that I could finally concentrate on master. We have enough regressions there, of various kinds, some 40-50 unit tests that did pass properly in the past. Various core changes that increase the accuracy of our library have the nasty side effect that they uncover certain assumptions. But let's not talk about master yet, and focus on the 1.4.15 release (download here). Unlike I had hoped, a lot changed since the 1.4.14 release.

I already mentioned this ENCODE discuthon we have next week. As I have to discuss stuff about hypersensitive DNA regions, I have to seriously brush up my biology. Brush up?? That suggests there was a decent basis. Well, think again. I though history was much more interesting!

I am a chemist. When people talk about the DNA in the cell, I always considered a single molecule. Until I learned there are 46 chromosomes. So, each cell actually has 92 DNA molecules.
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The CDK has been using PMD for quite a while yet, but there is another tool, called FindBugs. I had seen this before, but until I watched two Java Puzzler videos John sent me (here is one), I had not used that much. There is a nice Eclipse plugin, and you can run it on any Java package.

As I was procrastinating anyway (I should be preparing my core teaching qualifications portfolio and prepare a presentation on the accessibility of chromatin in the human genome, in an upcoming ENCODE discuthon.
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Since some time I have been member of the Open Science working group of the Open Knowledge Foundation. As such, I organized lunch meetings in Stockholm about Open Science (join this mailing list) and participated in working group efforts, such is running Is It Open Data (RIP) on the HCLS LODD data sets (many of them turned out to not be Open at all). Also, I love to have Open Science lunch meetings in Maastricht (and/or in Eindhoven), and if you do too, join this mailing list.

The adoption if InChI is increasing, despite its limitations. But one thing I find greatly missing, is chemical databases supporting access of entries via the appropriate InChI. I know there are resolvers around, but that is different. They do a search, and give me multiple links to individual structures that may match to a certain extend. I am not interested in that in this context.
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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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