NONLINEAR MODELING OF THE AIDS VIRUS GENETIC SEQUENCE EVOLUTION

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Abstract
A network of coupled maps is introduced to model the evolution of the genetic sequence of the HIV1 AIDS virus. Within a space of RNA chemical composition, short range interactions correspond to mutations. Ecological constraints generate long range couplings. The resulting equations are of a reaction-diffusion type. Quasi-species with an error threshold emerge from the model dynamics. Predictions relating chemical composition regularity properties with the variability of the HIV RNA sequence agree with a statistical analysis from gene data banks. The model suggests a clue for an alternative therapeutical treatment.

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