Abstract:Spatially-resolved datasets are revolutionizing knowledge in molecular biology, yet are under-utilized for questions in evolutionary biology. To gain insight from these large-scale datasets of spatial organization, we need mathematical representations and modeling techniques that can both capture their complexity, but also allow for mathematical tractability. Specifically, it is hard to link previous deme-based or lattice-based models with datasets exhibiting complex patterns of spatial organization and the ro… Show more
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