This is a very well written book on how to use cellular automaton, and especially Lattice-Gas-based Cellular Automaton (LGCA), to model various biological phenomena such as schools of fish, pigment distribution in salamanders and tumor growth. It is suitable for researchers interested in modeling pattern formation in general and CA, or Turing patterns, in particular. It is also well adapted for graduate (and advanced undergraduate) students, who have some background in partial differential equations, statistical mechanics (in particular Boltzmann's equation) and some programming. In places the biological background is a little brief (such as the introduction to cell sorting in 7.1 on page 144). Therefore some biological experience would be helpful. However good references to biological sources given, even though I could not find any general reference to development such as for example [1] or [4]. Another example where a reference would have been helpful is Table 2.1 on page 32 where a classification of organization principles is given. It would have been even more interesting if the authors had compared this to the classification made in [2].
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