Last week began with one of the regular meetings of the Chief Executives of MRC, EPSRC, BBSRC and the TSB with senior representatives of AstraZeneca, GlaxoSmithKline and Pfizer, along with representatives of the Bioindustry Association and the ABPI. This ‘Pharma Forum’ provides a useful vehicle for discussing cross-cutting research directions, especially given the net worth to the UK economy of the pharmaceuticals industry.
We also had one of the regular meetings of Chief Executives with Minister for Universities and Science David Willetts, which again provided a very useful forum for the exchange of thoughts on a variety of topical and strategic issues as we move towards the autumn statement.
I much enjoyed a ‘science’ day by attending the ‘TGAC Symposium on Bioinformatics’ held at the John Innes Centre. The (purposely) early career speakers covered a variety of very interesting topics, including the Bayesian analysis of ‘next generation’ sequencing (NGS) data (TJ McKinley, Cambridge), interspecies microbial metabolic interactions (Shiri Freilich, Agricultural Research Organisation, Tel Aviv), Population NGS data (Lachlan Coin, Imperial), genotype-phenotype mappings that do not require a reference genome (Zamin Iqbal, Oxford), protein structure estimation from sequences (Lucy Colwell, Princeton), memory-efficient analysis of NGS data (Quan Long, Gregor Mendel Institute) and machine learning approaches to uncovering small RNA function (Irina Mohorianu, UEA).
I was pleased to see BBSRC’s contribution to the sequencing and annotation of the pig genome (from Rasher with love?). What with the chicken and tomato genomes we have now almost done the full breakfast plate.
A very interesting paper describes a novel and biologically inspired approach to fast and low-power (‘green’) computing, while I also enjoyed a new tool for navigating very large (taxonomic and other) tree-structured data, some of the combinatorial effects of pesticides on bees that we funded (plus a commentary, and see an old blog predictions), a paper on data standards for exchanging aspects of innovation, and an analysis of 40 important questions around the means by which science can contribute usefully to policy (and to some degree vice versa).
I note an interesting crowd-sourcing strategy for improving the design of (US) patient records. Plausibly this could be extended to the design of other documents. Further regarding Open Data, a corpus of enzymes and metabolites for text mining that we previously used has been made available.
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