Welcome back to all from the winter break, to the first blog of 2012!

As last year, I attended part of the Oxford Farming Conference, where I enjoyed many excellent talks, such as one from USDA Chief Economist Joe Glauber highlighting the economic benefits to be had from investment in agricultural R&D and another from the newly knighted Defra Chief Scientist Sir Bob Watson. In informal conversation I also discovered the existence (from a young OFC Scholar) of the Miscanthus Growers Group. There is no doubt that improved and sustainable agricultural productivity is very much back on the scientific and agricultural agenda.

Since the last blog, among various press releases, we also published our impact report and provided a link to a video of the recently completed interim laboratory at the Institute for Animal Health.

I co-authored a couple of papers that were published towards the back end of last year, one using the methods of synthetic biology to produce Qconcat proteins for assessing the absolute concentrations of multiple proteins in parallel, and the other describing a toolbox of modules to assist (by semi-automating) the reconstruction of metabolic networks from suitable data such as those in KEGG. One example cited a speed-up from ca 1 year of work to ~4h! I was also pleased to have a new paper accepted for publication in an area I have been thinking about for a long time, viz. the idea that much if not all of scientific discovery is best seen as a combinatorial optimisation problem.

I enjoyed a nice paper to the effect that if one has many related protein sequences, that presumably tend to fold up the same way, there are therefore (overt or hidden but) powerful constraints that effectively tell you how they do so, thus speeding the means of proceeding from protein sequence to computer-calculated structure. I also draw attention to an important speech by Minister of Universities and Science David Willetts on the role of the Research Base and other contributors for “Our hi-tech future”. Certainly part of this might include doing more with what we have, and exploiting existing data is a worthwhile activity to this end. A nice paper in Science brings out some interesting new methods that are both principled and promising. Two others on literature mining describe an interesting method for connecting different papers to make a story and one analysing the benefits of candidate drug combinations, while another describes a fascinating data-driven approach to food pairing combinations in different cultures.

I was also pleased to see the recent discussion proposal (pdf) for the means of coding distributions or uncertainty in parameters as part of SBML models. Without these it is not so easy to estimate what the true ones might be via the measurement of experimental variables.

Finally, my attention was also drawn to an amusing two-part blog to the effect that “you know you’re a biologist when…”….at least some are likely to strike a chord!

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