Where are the paradigm shifts in biology?

Marc Robinson-Rechavi followed up in his blog on a post by Dan Graur about the use and abuse of “paradigm shifts” in biology

Dan is a bit cheeky with the way he uses “paradigm shift” as if in the “Kuhnian” sense. The articles he mentions that abuse the expression are not about Kuhn-like scientific revolutions. As far as I could understand from my readings, Kuhn’s paradigm shift is not a sudden result or discovery. It is the acceptance by the community of a new set of references. Kuhn’s paradigm shift is very much like Kimura’s substitution. Kimura’s substitution rate is not the rate of a molecular event at the level of DNA, but the rate at which this allele invades the population. Similarly, the paradigm shift is not itself a discovery or an article, although if often includes the common agreement of a few discoveries as key discrete events in a more continuous scientific revolution. The difference between Popper and Kuhn is that Popper draws a single continuous line of progress, while Kuhn draws a set of sigmoids, each one replacing the previous and hopefully explaining more of the world. This could be dispiriting because it means that whatever research you do, it will always come a time where it won’t be built on by future generations. However, it is important to note that past research is not erased. It is re-analysed within the context of the new paradigm. Newtonian mechanics is a limit-case of Einstein mechanics, Darwin’s natural selection is a new explanation of the earlier “transformism” etc.


Schematic view of scientific progress according to the Popper and Kuhn paradigm (ha ha …). The blue curves represent the increase of understanding of the world over time (by the entire population of scientists. I.e. it includes the pure increase of knowledge abd the increase of acceptance). The red dots are crucial discoveries/experiences/reinterpretations. Note that absolutely nothing in these drawings is random, from the slope of curves (which indicates the rate of new knowledge acquisition) to the position of the dots.

There were indeed several paradigm shifts in modern biology. Marc cited a few in the second part of his blog post (I believe the first part made the same mistake than Graur about the definition of paradigm shift).

One can also mention the shift from physiology – where one tries to explain quantitatively black-boxes (organs and cells) – to molecular biology – where one breaks the box and describe its components. Molecular biology really started between the two world wars, with the purification of proteins (Kossel), nucleic acids (Avery) etc. and became famous in the 1950s and 1960s with the description of the central dogma. However we are only talking about a few handfuls of scientists there. Of course so many of them got Nobel prizes (like a mutation hot spot, to continue on the genetic analogy). However, as a frame of reference to interpret the bulk of biological and biomedical data, we had to wait for the 1970s. In some fields, such as neuroscience, physiological thinking was still the orthodox point of view well into the 80s. Molecular biologists were then not considered as “real” neuroscientists, and their work deemed useless to explain the function of nervous system (interestingly an important factor in the shift came from dysfunctions. Because treating patient with molecules, that bound to pharmacological receptors, actually worked).

I believe we just witnessed another paradigm shift, from molecular biology – where one isolates a molecule, describes its structure and properties – to systems biology – where one puts back together all those molecules and try to understand how the behaviour of a system emerges from their interactions. Systems biology is of course not new. Systems theory originates from the beginning of XXth century and was used in physics soon after (cybernetics). In biology, interest started to arise in the 1960s, mostly in the field of metabolic network. However, the “systems allele” did not provide a better fitness than molecular biology and could therefore not invade the population (very little neutral evolution in science …). High-throughput data generation together with vast computational power and storage provided an altered environment that changed dramatically the fitnesses. Systems biology was “rediscovered” in the 90s and became the new frame of reference at the end of the last decade (under various guises, genomics, network biology, modelling etc.). A short personal view of systems biology history is given in one of my EBI courses.