Optimal Evolutionary Control for Artificial Selection on Molecular Phenotypes
Armita Nourmohammad,Ceyhun Eksin +1 more
TLDR
Optimal control for artificial selection offers a new paradigm for directing stochastic evolution of multivariate molecular characteristics and phenotypes toward desired targets.Abstract:
Optimal control for artificial selection offers a new paradigm for directing stochastic evolution of multivariate molecular characteristics and phenotypes toward desired targets.read more
Citations
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Antigenic waves of virus-immune coevolution.
TL;DR: In this article, the authors present a mathematical theory of coevolution between immune systems and viruses in a finite-dimensional antigenic space, which describes the cross-reactivity of viral strains and immune systems primed by previous infections.
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Shortcuts in Stochastic Systems and Control of Biophysical Processes
TL;DR: In this article , a graph-theoretic framework for counter-diabatic (CD) driving in discrete-state continuous-time Markov networks is presented, which allows for nonstationary targets and local control where only a subset of system states is targeted.
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Mechanisms underlying vaccination protocols that may optimally elicit broadly neutralizing antibodies against highly mutable pathogens
TL;DR: It is found that the characteristics of the time-varying Kullback-Leibler distance (KLD) between the B cell population distribution and the fitness landscape imposed by antigens is a key determinant of bnAb evolution.
Posted ContentDOI
Counterdiabatic control of biophysical processes
Efe Ilker,Özenç Güngör,Benjamin Kuznets-Speck,Joshua Chiel,Sebastian Deffner,Michael Hinczewski +5 more
TL;DR: In this article, the authors acknowledge support from the U.S. National Science Foundation (NSF) under Grant No. MCB-1651650 and the Labex CelTisPhyBioBioNitrome(ANR-11-LABX-0038, ANR-10-IDEX-0001-02).
Posted ContentDOI
Counterdiabatic control of biophysical processes
Efe Ilker,Efe Ilker,Efe Ilker,Özenç Güngör,Benjamin Kuznets-Speck,Benjamin Kuznets-Speck,Joshua Chiel,Joshua Chiel,Sebastian Deffner,Sebastian Deffner,Michael Hinczewski +10 more
TL;DR: In this article, a graph-theoretic framework for counter-diabatic (CD) driving in discrete-state continuous-time Markov networks is presented, with examples from gene regulation and chaperone-assisted protein folding.
References
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Journal ArticleDOI
The measurement of selection on correlated characters
Russell Lande,Stevan J. Arnold +1 more
TL;DR: Measures of directional and stabilizing selection on each of a set of phenotypically correlated characters are derived, retrospective, based on observed changes in the multivariate distribution of characters within a generation, not on the evolutionary response to selection.
Journal ArticleDOI
Bacterial Persistence as a Phenotypic Switch
Nathalie Q. Balaban,Nathalie Q. Balaban,Jack Merrin,Remy Chait,Lukasz Kowalik,Stanislas Leibler +5 more
TL;DR: Investigating the persistence of single cells of Escherichia coli with the use of microfluidic devices found phenotypic switching occurred between normally growing cells and persister cells having reduced growth rates, leading to a simple mathematical description of the persistence switch.
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PID control system analysis, design, and technology
Kiam Heong Ang,G. Chong,Yun Li +2 more
TL;DR: It is seen that many PID variants have been developed in order to improve transient performance, but standardising and modularising PID control are desired, although challenging, and the inclusion of system identification and "intelligent" techniques in software based PID systems helps automate the entire design and tuning process to a useful degree.
Journal ArticleDOI
Selection and covariance.
TL;DR: This is a preliminary communication describing applications to genetical selection of a new mathematical treatment of selection in general.
Journal ArticleDOI
Natural selection and random genetic drift in phenotypic evolution.
TL;DR: The concept of adaptive zones is clarified by the construction of an adaptive topography for the average phenotype in a population, which shows that with constant fitnesses theaverage phenotype evolves toward the nearest adaptive zone in the phenotype space, but if fitnesses are frequency-dependent the average phenotypes may evolve away from an adaptive zone.