Molecular biology, as does systems biology, relies heavily on the development of novel techniques for the study of biological systems and their subsequent exploitation. Thus, X-ray crystallography (Nobel Prize) for DNA structure determination (Nobel Prize), DNA sequencing (Nobel Prize), soft-ionisation mass spectrometry (Nobel Prize) for proteomics, PCR (Nobel Prize), and the Green Fluorescent Protein (and derivatives) for cell biology (Nobel Prize) have all revolutionized modern biology. In a similar vein, the discovery and use of restriction enzymes for molecular cloning (Lasker Prize) arguably initiated modern biotechnology. A considerable amount of BBSRC support continues to be aimed at basic molecular biology and biotechnology, and just last week we announced candidate swine flu vaccines produced using novel vectors, developed last year and this for rapid molecular engineering in plants, in the laboratory of George Lomonossoff and colleagues from the John Innes Centre. In this case the time from idea to exploitation was very swift, less than 2 years, but 15 years is more common! […]
The story of Goldilocks and the three bears is sufficiently well known not to need repeating here, its chief point for our purposes being that there was an optimum in everything she tried, whether it was the chairs, the beds or the porridge.
Chemical hormesis describes a similar set of phenomena in biology. To quote Calabrese (1997), “The concept of chemical hormesis has a long history, originating from the research of Schulz (1888) over a century ago who noted that many chemicals were able to stimulate growth and respiration of yeast at low doses yet were inhibitory at higher levels. This concept of a generalized low-dose stimulation/high-dose inhibition was gradually supported by similar observations with other chemicals and eventually became known as the Arndt-Schulz Law.” […]
The availability of many records in digital format opens up many possibilities, not least in bibliometrics, a subject that I anticipate will be a regular feature of these blogs. For this blog we are going to look briefly at the distribution of scientific activity between individuals, as encapsulated by the question ‘if n individuals have published 1 scientific paper in a particular time period, how many individuals have published 2 papers or 10 papers or 100 papers?’
Now one might wonder whether one should expect there to be any regularities in such a (quantised) distribution, but there are. The question was posed and answered most pertinently by Alfred Lotka in 1926, and the relationship is known as Lotka’s Law. Lotka observed, from a study of papers listed in Chemical Abstracts and in Auerbach’s Geschichtstafeln der Physik, that the number of persons making n contributions is given by 1/na of those making a single contribution, with a equalling approximately 2. Thus for every 100 people who have published 1 paper, 25 have published 2 papers and 1 person has published 10 papers. In other words, the distribution of scientific productivity is best described by an inverse square law (a specific version of a negative exponential more generally referred to as a Zipf distribution). Although this is not universally true, it is a reasonable approximation and has some interesting mechanistic bases. The consequences, as recognised in Lotka’s original survey, included the fact that 60% of contributions were made by authors who contributed only one paper (and note that all joint papers were taken to have been written by the ‘senior’ author only). Nowadays this would be seen as a long-tail phenomenon, as popularised in Chris Anderson’s excellent book. […]
‘How systems work’ is already a theme of these blogs, in that the general properties of systems – typically seen (mathematically) as ‘graphs’ of objects that interact with each other – are assumed by definition to have general applicability. While our focus is normally on biology, it is assumed from a systems perspective that the rules that we learn in biology can hopefully similarly be applied to other systems, and vice versa. One such class of system is the domain of what Carlyle famously called the ‘dismal science’ of economics – on which everyone, however amateur, is a Monday morning quarterback (and at some level a participant). So one of the books I read in the holidays was Paul Krugman’s short and masterful analysis of the lead-up to and unfolding of the present economic downturn. Now Krugman is no slouch – the book is an update of his predictions in 1999, and he received the Nobel Prize in Economics for 2008 – and his writing style is simple, effective, jargon-free and understandable. Some of his main conclusions (as I take them) are equivalently simple: […]