Thus, we see large divergences between different cell types, which have specific functions. Throughout development these acquire identities involving individual differentiation. All cells and tissues of an organism arise from a primordial cell. The information encoded in the DNA of cells is the same for each cell of an organism. 33).Įpigenetics in this context are all those factors involved in the regulation of DNA that do not involve changes in the sequence (Waddington, 1962 Jablonka and Lamb, 2015). However, Waddington's concept was designed as “a true synthesis between developmental processes and genetic action, which together bring the organism into being” (Van Speybroeck et al., 2002, p. In the 1950s and 1960s as proposed by Waddington it was seen as a competitor to genetics. Epigenetics is now a broadly accepted aspect of genetics. We apply his model in the first place to epigenetic processes, which we understand in a broad sense, to refer to all mechanisms which act on the realizations of genetic action, not just to heritable DNA-modifications such as methylation. ( 1984), that they produce chaos (unlimited and unpredictable diversity) as well as complexity. In this respect he was adding a new requirement for complex biological models like those of Maturana et al. Conway did not refer to this work but he implemented the principle, stating that “the rules should be such as to make the behavior of the population unpredictable.” He was not simply modeling any elemental biological system, he was modeling indeterminate chaos. Lorenz ( 1995) and Eckmann and Ruelle ( 1985) proposed a three dimensional system as fitting this specification. One interesting feature of this class of model is that it incorporated a general principle that later became a major factor in chaos theory, the idea of “deterministic chaos”: that is, the smallest number of rules which could generate an inherently unpredictable system. In the process we can understand better what deeper biological principles are being modeled in this simulation. In that way we can test whether the game has a heuristic function, the capacity to develop new explanations which were not envisaged in the initial design. Yet for heuristic purposes it is equally important to apply it to phenomena which were not part of the original intention. This purpose explains the interest of this game for biologists, since it explicitly aims to model a basic process in biology, the evolution of ecological communities (see Caballero et al., 2014). We show how this crucial function for practicing scientists can be found in the strategic use of versions that are usually dismissed by scientist as trivial and unserious.Ĭonway made connections with biology part of his purpose, bringing out “analogies with the rise, fall and alternations of a society of living organisms” (Gardner, 1970). We see this second purpose, its “heuristic” or discovery function, as especially productive for biology. In this article we explore the merits for these purposes of a simulation game called “Life” by its creator, John Conway, “the Game of Life” by others. They provide judgment on the strengths of competing hypotheses, and generate unexpected or unsuspected possibilities for biologists to study and prove empirically. In recent times, computer simulations have played an increasingly important role in biology, in testing hypotheses and generating new ones. We use the game to explore issues in symbiopoiesis and evo-devo, where we explore a fractal hypothesis: that self-similarity exists at different levels (cells, organisms, ecological communities) as a result of homologous interactions of two as processes modeled in the Game of Life We show the value of computer simulations to experiment with and propose generalizations of broader scope with novel testable predictions. We look for similarities and differences between two epigenetic models, by Turing and Edelman, as they are realized in Game of Life objects. We show that Conway's organization of rules reflects the epigenetic principle, that genetic action and developmental processes are inseparable dimensions of a single biological system, analogous to the integration processes in symbiopoiesis. We apply it to other biological processes, including symbiopoiesis. This game was designed to explore the evolution of ecological communities. Conway's Game of Life has been widely used for this purpose.
Cellular automatons and computer simulation games are widely used as heuristic devices in biology, to explore implications and consequences of specific theories.
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