A mechanistic model with horizontal gene transfer, new gene capture, genome emergence, and gene loss generates scale-free gene degrees and exponential genome degrees in bipartite networks, closely matching viral and pangenome observations when gene loss rate is set to zero.
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Temporal correlations in token sequences decouple type-token growth curves from rank-frequency distributions, with a one-parameter model reproducing the range of possible trajectories for any given frequency distribution.
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A generative model for bipartite gene-sharing networks
A mechanistic model with horizontal gene transfer, new gene capture, genome emergence, and gene loss generates scale-free gene degrees and exponential genome degrees in bipartite networks, closely matching viral and pangenome observations when gene loss rate is set to zero.
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The dynamics of discovery and the Heaps-Zipf relationship
Temporal correlations in token sequences decouple type-token growth curves from rank-frequency distributions, with a one-parameter model reproducing the range of possible trajectories for any given frequency distribution.