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19952023
most citedQuasispecies Theory for Multiple-Peak Fitness Landscapes

70 citations · 427 across the 46 of their papers we have counts for

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9 papers · 1 filter

q-bio.PE2022

The non-perturbative phenomenon for the Crow Kimura model with stochastic resetting

R. Poghosyan, R. Zadourian, David B. Saakian

We consider the Crow Kimura model, modified via stochastic resetting. There are two principally different situations: First, when due to resetting the system jumps to the low fitne…

q-bio.PE2020★ 5 cited

A simple statistical physics model for the epidemic with incubation period

David B. Saakian

Based on the classical SIR model, we derive a simple modification for the dynamics of epidemics with a known incubation period of infection. The model is described by a system of i…

q-bio.PE2012★ 16 cited

Finite population size effects in quasispecies models with single-peak fitness landscape

David B. Saakian, Michael W. Deem, Chin Kun Hu

We consider finite population size effects for Crow-Kimura and Eigen quasispecies models with single peak fitness landscape. We formulate accurately the iteration procedure for the…

q-bio.PE2012★ 13 cited

Biological Evolution in a Multidimensional Fitness Landscape

David B. Saakian, Zara Kirakosyan, Chin-Kun Hu

We considered a {multi-block} molecular model of biological evolution, in which fitness is a function of the mean types of alleles located at different parts (blocks) of the genome…

q-bio.PE2012★ 11 cited

Finite genome length corrections for the mean fitness and gene probabilities in evolution models

Zara Kirakosyan, David B. Saakian, Chin Kun Hu

Using the Hamilton-Jacobi equation approach to study genomes of length , we obtain 1/L corrections for the steady state population distributions and mean fitness functions for h…

q-bio.PE2009

The optimization and shock waves in evolution dynamics

David B. Saakian, Jose F. Fontanari

We consider the optimal dynamics in the infinite population evolution models with general symmetric fitness landscape. The search of optimal evolution trajectories are complicated…