Chemical and biological laboratories produce information in a large number of forms and for a variety of purposes. This diversity often works against the adoption of one-size-fits-all solutions, and can significantly increase the costs of creating custom systems. One approach to this problem focuses on creating interoperable components that can be reused in a variety of contexts.

Although autonomous Robot Scientsts will probably not be appearing in quantity for some time to come, many labs already host an impressive array of automated technologies used in connection with chemical research. Much of this equipment consists of an autosampler attached to an instrument such as an NMR spectrometer, a mass spectrometer, a chromatogram, or a preparative chromatography system.

Although it may not be readily apparent, the early history of scientific publishing has much to teach in the Internet age. Look on the desk of any working research chemist and you’re likely to find at least one of these three items: (1) The CRC Handbook; (2) The Aldrich Catalog; and (3) The Merck Index. It may be no accident that all three of these iconic reference works trace their roots to marketing.

The Chem Blog recently discussed the usability of computational chemistry software as seen through the eyes of a research chemist. A highlight: I’ll freely admit to knowing very little about computational chemistry software (a situation I hope to change). And as a synthetic organic chemist who worked in industry for several years, I tend to agree with the sentiment above. On the other hand, we had people who we paid to do these things for us.

The twentieth installment of the Sixty-Four Free Chemistry Databases series has recently been added.

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Ein Fehler ist aufgetreten. Sieh dir dieses Video auf www.youtube.com an oder aktiviere JavaScript, falls es in deinem Browser deaktiviert sein sollte. Nico Adams and Jim Downing offer a fascinating look at what linked data can do for chemistry, what’s possible now, and the barriers that still need to be crossed.

The applications of graphs in cheminformatics are numerous. From modeling molecules themselves to reaction networks, to ring system indicies, and even scientific paper authorship relationships, graphs are the way most problems get framed. Wouldn’t it be great if your natural mental model of a problem didn’t have to change just because you needed persistent storage of the underlying data?

The Chemcaster Web API documentation is now online. For the unfamiliar, Chemcaster is the cheminformatics Web services platform optimized for rapid creation of chemistry-focussed websites.

It’s been said before but bears repeating: social networking is a feature, not a destination. One service that demonstrates this principle very well is GitHub, which not only lets you keep track of specific repositories a given developer is maintaining, but their activity on GitHub in general. This can be very useful in finding new software, learning about new approaches, and meeting other developers that share your interests.

The second beta release of MX is now available for download. MX is a library of essential cheminformatics models and routines. It was created with the goal of providing a clean, well-tested platform for chemistry applications. This beta release includes a new binary fingerprinter package that was not ready for release in the first beta.