Formalizes interventions on EvAMs via Pearl's do-operator for multiple model types, distinguishes killing versus inactivating interventions, and supplies ranking protocols for target prioritization.
Darwinian evolution can follow only very few mutational paths to fitter proteins , Volume =
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In isotropic Gaussian random field fitness landscapes the expected number of local optima is determined by the correlation of fitness effects, with modularity increasing and locus heterogeneity decreasing the count.
citing papers explorer
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A structural causal framework for interventions on evolutionary accumulation models
Formalizes interventions on EvAMs via Pearl's do-operator for multiple model types, distinguishes killing versus inactivating interventions, and supplies ranking protocols for target prioritization.
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Epistatic strength, modularity, and locus heterogeneity shape the number of local optima in fitness landscapes
In isotropic Gaussian random field fitness landscapes the expected number of local optima is determined by the correlation of fitness effects, with modularity increasing and locus heterogeneity decreasing the count.