  The genetic composition of a naturally developing population is considered as
due to mutation, selection, genetic drift and recombination. Selection is
modeled as single-locus terms (additive fitness) and two-loci terms (pairwise
epistatic fitness). The problem is posed to infer epistatic fitness from
population-wide whole-genome data from a time series of a developing
population. We generate such data in silico, and show that in the Quasi-Linkage
Equilibrium (QLE) phase of Kimura, Neher and Shraiman, that pertains at high
enough recombination rates and low enough mutation rates, epistatic fitness can
be quantitatively correctly inferred using inverse Ising/Potts methods.
