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Luminescence by diffusion rule. We will work along three main lines: Therefore, our work focuses on molecular computation. Aranda Barradas jaranda acei.

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CA governed by such cell-state transition rule exhibits reaction-diffusion like pattern dynamics, so we call this Diffusion Rule. We thus have three models using cellular automata theory you can see our original contributions click here.

Cell in state 0 takes state 1 if there are exactly two neighbors in state 1, otherwise the cell remains in state 0. We intend to emulate some genetic networks already identified in Arabidopsis responsible for the formation of hair in root and leaves.

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Cell in state 1 remains in state 1 if there are exactly seven neighbors in state 1, otherwise the cell switches to state 0. We study two-dimensional cellular automaton, where every cell takes states 0 and 1 and updates its state depending on sum of states of its 8 closest neighbors as follows.

The system is created defining an inicial state over the base configuration see figure 3. Also, they are capable of supporting universal computation, self-repair and self-reproduction.

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We wish contribute to the iGEM project development various protein based bio-components. We are attempting to construct discrete dynamical systems capable of simulating cellular computation.

Starting with any configuration, the cells alive are represented in yellow the activator and dead in black the inhibitorsee figure 4. We aim to develop CA software for a specific bio-simulation and gradually implement broader real biological scenarios.

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Cellular automata CA operate over a scales ranging from the molecular level to n-dimensions and are massively parallel. The luminescence is obtained by the evolution of this initial pattern. We would like to show that these systems support Turing patterns. Developing models to describe inside-the-cell metabolic events through a cellular automata approach.

Gordillo Padilla extraterrestre hotmail. Physics Line of Investigation Our main line of investigation uses unconventional computing as a means of building novel computing paradigms, such as in biology, physics and chemistry.