activity
20092020
most citedFrom genotypes to organisms: State-of-the-art and perspectives of a cornerstone in evolutionary dynamics

110 citations · 189 across the 5 of their papers we have counts for

collaborators

5 papers

q-bio.PE2020★ 110 cited

From genotypes to organisms: State-of-the-art and perspectives of a cornerstone in evolutionary dynamics

Susanna Manrubia, José A. Cuesta, Jacobo Aguirre +15

Understanding how genotypes map onto phenotypes, fitness, and eventually organisms is arguably the next major missing piece in a fully predictive theory of evolution. We refer to t…

cond-mat.dis-nn2011

Direct, physically motivated derivation of triggering probabilities for spreading processes on generalized random networks

Kameron Decker Harris, Joshua L. Payne, Peter Sheridan Dodds

We derive a general expression for the probability of global spreading starting from a single infected seed for contagion processes acting on generalized, correlated random network…

physics.soc-ph2011★ 18 cited

Exact solutions for social and biological contagion models on mixed directed and undirected, degree-correlated random networks

Joshua L. Payne, Kameron Decker Harris, Peter Sheridan Dodds

We derive analytic expressions for the possibility, probability, and expected size of global spreading events starting from a single infected seed for a broad collection of contagi…

cond-mat.dis-nn2011

Direct, physically-motivated derivation of the contagion condition for spreading processes on generalized random networks

Peter Sheridan Dodds, Kameron Decker Harris, Joshua L. Payne

For a broad range single-seed contagion processes acting on generalized random networks, we derive a unifying analytic expression for the possibility of global spreading events in…

physics.soc-ph2009★ 61 cited

Analysis of a threshold model of social contagion on degree-correlated networks

Peter Sheridan Dodds, Joshua L. Payne

We analytically determine when a range of abstract social contagion models permit global spreading from a single seed on degree-correlated random networks. We deduce the expected s…