266 and a complete circle rule. It could explain a number of complex regeneration experiments, but made assumptions which were hard to connect to known molecular mecha- nisms and simple morphogen models. Meinhardt realised that an organiser region defined by the crossing of an anterior–posterior and a dorsoventral compartment would provide the same explanatory power as the polar coordinate model and, in addition, could be linked to the recent discovery of compartments as clonally restricted groups of cells in Drosophila (Meinhardt 1983). Such insights were not dependent on particular local activation-lateral inhibi- tion equations, but rather were derived from the attempt to find a minimal realistic model which could explain complex phenomena. The basic correctness of Meinhardt’s ideas were acknowledged 12 years later after the molecular mechanisms of the predicted compartment interactions had been discovered (Vincent and Lawrence 1994). The second example concerns stripe formation. Meinhardt and Gierer had recognised that certain types of patterns were difficult to simulate with a lateral inhibition mechanism (Meinhardt and Gierer 1980). In particular, this applied to stripe formation, an important prerequisite to understand segmentation. To produce stable stripes they introduced the idea of lateral activation of mutually exclusive states. Two cell states each producing an autocatalytic substance ex- change signals which mutually promote their autocatalysis. Thus, they can only exist next to each other. However, they also stay separated since each cell state locally inhibits the other state. This model made stripe formation possible and thus, Meinhardt used it to simulate segmentation. Much later and without reference to the early work, this mechanism was rediscovered as the core kinetics of the Drosophila segment polarity network (von Dassow et al. 2000). It is of particular interest that the new simulations did not start with a specific kinetic model, but used model equations entirely based on experimental data and the assumption of robustness to identify relevant parameter sets. Thus, remarkably, an unbiased, data-driven approach discovered an intricate mechanism, which had been suggested entirely on theoretical grounds. The third example refers to colour patterns on the surface of sea shells (Meinhardt and Klinger 1987). Here, it is not so much the particular logic of a mechanism which made the simulations attractive, but the sheer similarity, indeed frequently the complete accordance, of highly complex patterns with the computer-generated images (Meinhardt 2009). It seemed that an agreement between natural pattern and simulation, capturing so many details, could not be accidental. One was forced to assume that the theory has captured at least some correct aspects of the underlying patterning mechanisms. Recently, the same shell patterns have been simulated using a neurosecretory model sup- ported by experimental findings on the anatomy of the Dev Genes Evol (2011) 221:255–279 mollusc mantle, the shell-making machinery (Boettiger et al. 2009). The neural circuitries used in this model combine local activation and lateral inhibition and thus demonstrate the equivalence between different molecular and cellular realisations of the Gierer–Meinhardt model. However, they also provide a clue about how difficult it is to predict the actual nature of the mechanisms underlying a patterning process even if the simulations recover the output pattern with astonishing accuracy. The rise of Drosophila developmental genetics In the early 1970s, when Meinhardt and Gierer formulated their model on the basis of, and in close contact with, the experiments on hydra conducted in Gierer’s department, the theory seemed to be close to the biological phenomena. The members of the research group felt that it was only a matter of time until they had isolated the autocatalytic activator(s) and the broadly diffusible long-range inhibitor(s). The first candidates had been already purified (Schaller and Gierer 1973; Schaller 1973). A splendid validation of the theoretical work seemed imminent. However, this turned out to be much more difficult than expected. Even today, the regulatory behaviour of hydra is not fully understood at the molecular level, and the postulated diffusible activators and inhibitors have not been identified (Bode 2009). It transpired that biochemical methods were much less powerful for the dissection of developmental pathways than expected. In the atmosphere of early enthusiasm about pattern formation theory and its molecular validation, Christiane Nüsslein-Volhard obtained her Ph.D. on bacteriophage transcription, not with Gierer, but in the neighbouring department of Gerhard Schramm (under the supervision of Heinz Schaller). In a contribution to a symposium in honour of the Gierer’s 80th birthday, Nüsslein-Volhard recalls that she was fascinated by the work on hydra and that the theoretical work on morphogen gradients influ- enced her thoughts and her choice to pursue embryonic pattern formation as a postdoc (Nüsslein-Volhard, personal communication). Nüsslein-Volhard, however, chose a ge- netically accessible system, Drosophila melanogaster. She joined Walter Gehring’s group in Basel, and in a short time characterised two maternal-effect mutants which were involved in setting up morphogen gradients in the early Drosophila embryo, bicaudal and dorsal (Nüsslein-Volhard 1979a; Nüsslein-Volhard 1979b). In the discussion of her first Drosophila paper, the description of the bicaudal mutant, the influence of the Tübingen theory group can clearly be felt. She favours the Gierer–Meinhardt model compared to other explanations for the bicaudal phenotypic series: ‘Although this model probably does not account for