264 forming ‘in apparently uniform areas such as the wings of butterflies, the shells of molluscs, the skin of tigers, …’ (ibid). He ends his letter by describing the question in embryology which he finds most pressing to be ‘tackled from a mathematical point of view’ (ibid): the occurrence of ‘a finite number of definitely distinct tissues and organs…’ (ibid). How is it avoided that intermediate states emerge? How does the selection between discrete states take place? Waddington alludes here to a type of genetic network theory, a theory which does not explain patterning in physical space, but within the state space of a network of interacting genes. From the remarks in his letter, it is apparent that he had started to work on such a theory. In 1954, he published a paper where he proposed a system of two autocatalytic gene products that consume the same substrates and thus enter into a competition resulting in distinct stable states. He also considers a direct interaction of the autocatalytic gene products and compares the resulting system with ‘two populations of animals which compete with one another for a limited food supply’ (Waddington 1954). Lotka’s work is cited for the mathematical treatment of this situation. In the following years, Brain Goodwin did his Ph.D. thesis in Waddington’s laboratory and extended the theory to systems with many components and stochastic fluctuations. He called his ideas epigenetic thermodynamics (for a brief summary see Waddington 1962, 45–50). Despite his criticism, Waddington was one of the few biologists who did take notice of Turing’s work. He summarised Turing’s results in his writings (e.g. Waddington 1956, 422; Waddington 1962, 125–130) and thereby made it known to other scientists. Another exception was John Maynard Smith, who used Turing’s idea of chemical waves to explain modal variations in populations (i.e. the occur- rence of fixed integers of anatomical structures like the five fingers of the hand, Maynard Smith 1960). In 1968, he wrote a small book on Mathematical Ideas in Biology which ends with a beautifully written, lucid account of Turing’s ideas. Nevertheless, in the first 10 years after its publication, Turing’s paper was cited fewer than two times per year (Nanjundiah 2003) and it remained largely unknown throughout the 1960s, even to developmental biologists. In part, this was due to a shift of research focus in modern biology. The discovery of the DNA structure in 1953 immediately led to a number of central questions such as deciphering the genetic code, understanding translation, etc. and thus opened up completely new research areas which were evidently crucial for an understanding of life. Physicists and chemists preferred to enter the new field of molecular biology rather than working on theoretical and mathematical modelling of biological phenomena which were not under- stood at the cellular or molecular level. In addition, there was a high demand for scientists with a physics and mathematics Dev Genes Evol (2011) 221:255–279 background in the early days of molecular biology both with regard to their experimental (e.g. for X-ray crystal- lography) and their conceptual (e.g. for deciphering the genetic code) skills. There were also intrinsic reasons, however, for why Turing’s work played only a marginal role even among the few developmental biologists who continued their work in the shadow of the molecular revolution. In his letter to Turing, Waddington had already pointed out what later would be viewed as the most significant deficit of Turing’s work: the fact that it did not explain self-regulation (see also Waddington 1956, 422f). A general belief was formed that reaction-diffusion mechanisms are unable to account for such phenomena. Wolpert’s introduction of the concept of positional information had spurred a renewed interest in self-regulation and scaling (Wolpert 1969). A typical feature of patterns produced by a positional information mechanism was size invariance. Wolpert used the French flag analogy to illustrate this point: the relative sizes of the blue, white and red areas of a French flag remain the same irrespective of the absolute size of a particular flag. He found Turing’s chemical waves ‘not very satisfactory’ even to explain the pattern of bristles on the insect cuticle, and much less so to account for positional information in general (Wolpert 1969). Rather, he was attracted by the highly complex theory of Goodwin and Cohen (1969), who stated: ‘Turing-type periodic waves remain a possibility, but the problem of regulation for such a model is severe’. Their own proposal was based on very specific, but largely unsupported biological assumptions. They derived posi- tional information from the phase difference between coupled cellular oscillators. Nevertheless, their phase-shift model was more popular among theoretically inclined biologists than Turing’s ideas, largely because it offered a solution to the mysterious problem of scaling. In the mid-1960s, an outline of the basic molecular mechanisms of life (replication, transcription, translation) had been attained and some of the pioneers of the molecular revolution were looking for new challenges. More complex biological phenomena such as multicellular development and neurobiology attracted their attention. Alfred Gierer was one of these pioneers. He had received a Ph.D. in theoretical physics with work on proton transfer across hydrogen bonds and the theory of liquids. Pauling’s book The nature of the chemical bond and the work on the α- helix had motivated Gierer to enter biology. In 1954, he started to work in Tübingen at the Max-Planck-Institute of Virus Research on the RNA of the Tobacco Mosaic Virus and in the following years demonstrated that not only DNA, but also RNA can be a carrier of genetic information. After some work on protein synthesis in the early 1960s, his group shifted to developmental biology, focusing on hydra as a model system which, in particular, allowed them