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When simulating biological populations under different evolutionary geneticmodels, backward or forward strategies can be followed. Backward simulations,also called coalescent-based simulations, are computationally very efficient.However, this framework imposes several limitations that forward simulationdoes not. In this work, a new simple and efficient model to perform forwardsimulation of populations and/or genomes is proposed. The basic idea considersan individual as the differences (mutations) between this individual and areference or consensus genotype. Thus, this individual is no longer representedby its complete sequence or genotype. An example of the efficiency of the newmodel with respect to a more classical forward one is demonstrated. Thisexample models the evolution of HIV resistance using the B_FR.HXB2 referencesequence to study the emergence of known resistance mutants to Zidovudine andDidanosine drugs

Simulating Genomes and Populations in the Mutation Space: An example with the evolution of HIV drug resistance