Fast molecular similarity with a new 3D shape descriptor

Jim reported about SPECTRa being in the news and ./ about Toward a 3D Search Engine. These two items have in coming that they deal with the article Ultrafast shape recognition for similarity search in molecular databases by Ballester and Richards (DOI:10.1098/rspa.2007.1823). The NewScientist wrote up their angle on it, with a quote from Henry Rzepa.

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Nature Network v2: cannot create a new group

Nascent reported that Nature Network v2 has gone life. Never too anxious to try something new, I created an account and signed in. I even joined two groups: Bioinformatics and Semantic Web for the Life Sciences.

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Invisible InChI's

Some InChI’s are short, such as that for methane: InChI=1/CH4/h1H4. Others are long (think crambin), and you don’t want to show them inline. Or you just want to show them anyway, but still want the chemistry to be understood. Here come the invisible InChI’s.

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Pimp my JavaDoc

Jörg’s PhD book Data Mining und Graph Mining auf molekularen Graphen - Chemoinformatik und molekulare Kodierungen für ADME/Tox-QSAR-Analysen has a dump of the JavaDoc of the GroupContributionPredictor in JOELib (Figure 3.2, page 43). There are two nice things to the shown JavaDoc: 1. it has links to Wikipedia; 2. it has a Further Reading section.

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Is that Jmol in that D-Wave demo?

Slashdot reported on D-Wave’s recent demo of their 16-qubit quantum computing system. Video’s of the demo can be watched on Google Video. The second video demonstrates the use of the machine in similarity searching:

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Writing up my PhD introduction chapter...

The last twelve months or so, I have been doing two jobs (excluding hobbies of mine, such as Chemical blogspace): my postdoc in the group of Christoph Steinbeck on computer aided structure elucidation, and finishing my PhD. The topic of my PhD is about the interplay between chemoinformatics and chemometrics: the first being strong in dealing with molecular structures, the latter strong in data analysis and mining, originally on experimental data. Really, I focused on a few existing problems, such as how to represent and analyze large libraries of crystal structures, the use of NMR spectra in QSAR studies, and two more practical problems regarding reproducibility of scientific results, which includes communication of data, and transferability of algorithms. Actually, I also studied fragment mining in QSAR for a set of transfactants, but that has not lead to firm results yet.

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CDK Workshop - Days #3 and #4

Days #3 and #4 of the CDK Workshop have been quite busy indeed, and I have not been able to summarize them so far. After a rather interesting day #2, the third day was the last one with scheduled presentations. Kai Hartmann showed how he used the CDK in his systems biology research, and contributed the code he wrote to predict Gibbs energies based on fragment contributions. Miguel Rojas showed his MS prediction work, which is based on the CDK too.

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