Friday, 20 November 2009

say what you mean

Earlier this month, Sue Keogh gave a seminar entitled “Seven Steps to Great Web Copy” at the EBI. Good thing that EBI Interfaces published a round-up including the presentation and some useful notes. Most of it is just plain common sense (“it’s actually harder to be concise than to write a load of waffle”), but how many science-related websites actually use the common sense?

Thursday, 19 November 2009

not just drug design

Drug Design: Cutting Edge Approaches, published in 2002, is a collection of highly enlightening reviews, even if some of the approaches may be not so cutting-edgey any longer. (Really, one should never name a book like that.) The two chapters authored by Darren Flower (who is also an editor of the book) are a pleasure to read, not least because they put the drug design into fascinating historical and philosophical context.

From Molecular informatics: Sharpening drug design’s cutting edge:
‘Show me a drug without side effects and you are showing me a placebo,’ a former chair of the UK’s committee on drug safety once commented. As pharmaceutical products, of which Viagra is the clearest example, are treated more and more as part of a patient’s lifestyle, the importance of side effects is likely to grow. A recent study concluded that over 2 million Americans become seriously ill every year, and over 100,000 actually die, because of adverse reactions to prescribed medications.
On bioinformatics:
Academic bioinformaticians sometimes seem to lose sight of their place as an intermediate taking, interpreting, and ultimately returning data from one experimental scientist to another. There is a need for bioinformatics to keep in close touch with wet lab biologists, servicing and supporting their needs, either directly or indirectly, rather than becoming obsessed with their own recondite or self referential concerns.
On molecular similarity:
There is, ultimately, no ‘gold standard’ by which to judge the performance of different similarity measures. There is no consensus between chemists, or computer algorithms, and there isn’t one between receptors either. There is no universally applicable definition of chemical diversity, only local, context-dependent ones. The only correct set of rules would be those that a receptor chooses to select molecules: but these will vary greatly between different receptors. This has not discouraged the development of a large literature — comparing methods, primarily in the context of justifying the apparent superiority of a method that the authors have developed; these are often large, complex, yet discombobulatingly terse papers which assaults the reader with the weight of information rather than the arguments of sweet reason.
From Computational vaccine design:
Death, the pale horseman, comes in many guises, covering diverse causes from individual natural disasters to accidental injury. Natural disasters, or what insurance brokers are pleased to call acts of god, would figure highly on the average individual’s list of greatest causes of death and destruction.
One of the most significant events in the history of human disease interaction was the new world holocaust that affected South America in the century or so after its ‘discovery’ by the Spanish. <...> The catastrophic decline in the indigenous Indian population was on a scale unmatched even in the 20th century, and was likely to have been the greatest ever loss of an aboriginal population.
Drug Design: Cutting Edge Approaches

Monday, 9 November 2009

twenty years after

Just finished watching the BBC broadcast from Berlin, with giant dominoes falling and all that. I remember the euphoria at the time. Nowadays it is difficult to imagine anyone in right mind who’d say that the fall of the Berlin Wall was a bad thing. (Margaret Thatcher was famously opposed to it, but I am not sure she was in right mind.)

Still, I didn’t expect yesterday’s article in Guardian by Bruni de la Motte to cause such a torrent of (mostly right-wing) comments.

As a result of the purging of academia, research and scientific establishments in a process of political vetting, more than a million individuals with degrees lost their jobs. This constituted about 50% of that group, creating in east Germany the highest percentage of professional unemployment in the world; all university chancellors and directors of state enterprises as well as 75,000 teachers lost their jobs and many were blacklisted.
I don’t know how correct are the figures, but the article rings the right bells to me. Some of my colleagues from former GDR have lost their jobs as a result of Abwicklung (restructuring, or rather liquidation, of East German institutions). I think the biggest loser here was German science as a whole: East German scientists, educated to a high standard, had no problem finding jobs in the USA. But then, social revolutions, even velvet ones, are rarely good news for science.

Brigitte Young wrote in her 1993 paper:

Women are not only the first to lose their positions in the process of Abwicklung, they are also the last to be considered in the new stage of rebuilding the university system. Thus the politics of Abwicklung has to be understood as a microcosm of the gendered nature of German unification as a whole. Unification has provided German conservatives the opportunity to roll back not only the social policies of the east, but also the feminist achievements in the west.
But that was 16 years ago, right? Surely by now things should have got better. Yet the East-West divide still exists in German science. (In words of Fritz Stern, “the physical wall has been internalized”.) In last week’s Science, Gretchen Vogel wonders why the Max Planck Society, out of its 267 directors, has only one former East German who started a career before 1989. Not that it has many women directors either. Christiane Nüsslein-Volhard, Director at the Max-Planck-Institute of Developmental Biology, wrote that
in 1995, the society was able to boast that 25% of their female directors had received a Nobel prize.