A Gene Network Model of Resource Allocation to Growth and Reproduction
Sloan Center for Theoretical Neurobiology, The Salk Institute
Machine Learning Systems Group, Jet Propulsion Laboratory
We present a model of optimal allocation of resources to reproduction and growth in a simple multicellular organism, using a gene network formalism to simulate gene interactions within cells. The model is compatible with more conventional approaches to allocation problems in life history and in addition provides connections between processes at the gene and cell levels on one hand and life history strategies on the other. The model may also offer an example of how a genotype orchestrating development imposes constraints on the optimal solutions that evolution can reach.
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