Search results for "Quantitative Biology::Populations and Evolution"

showing 10 items of 138 documents

"21-B2_3" of "Multiplicity dependence of light (anti-)nuclei production in p-Pb collisions at $\sqrt{s_{\rm{NN}}}$ = 5.02 TeV"

2019

Coalescence parameter $B_2$ as a function of $p_{\mathrm{T}}$ in the 20-40% V0A multiplicity class

$B_{2}$Quantitative Biology::Populations and Evolution
researchProduct

"20-B2_2" of "Multiplicity dependence of light (anti-)nuclei production in p-Pb collisions at $\sqrt{s_{\rm{NN}}}$ = 5.02 TeV"

2019

Coalescence parameter $B_2$ as a function of $p_{\mathrm{T}}$ in the 10-20% V0A multiplicity class

$B_{2}$Quantitative Biology::Populations and Evolution
researchProduct

"22-B2_4" of "Multiplicity dependence of light (anti-)nuclei production in p-Pb collisions at $\sqrt{s_{\rm{NN}}}$ = 5.02 TeV"

2019

Coalescence parameter $B_2$ as a function of $p_{\mathrm{T}}$ in the 40-60% V0A multiplicity class

$B_{2}$Quantitative Biology::Populations and Evolution
researchProduct

"19-B2_1" of "Multiplicity dependence of light (anti-)nuclei production in p-Pb collisions at $\sqrt{s_{\rm{NN}}}$ = 5.02 TeV"

2019

Coalescence parameter $B_2$ as a function of $p_{\mathrm{T}}$ in the 0-10% V0A multiplicity class

$B_{2}$Quantitative Biology::Populations and Evolution
researchProduct

"23-B2_5" of "Multiplicity dependence of light (anti-)nuclei production in p-Pb collisions at $\sqrt{s_{\rm{NN}}}$ = 5.02 TeV"

2019

Coalescence parameter $B_2$ as a function of $p_{\mathrm{T}}$ in the 60-100% V0A multiplicity class

$B_{2}$Quantitative Biology::Populations and Evolution
researchProduct

Dynamic complexities in host-parasitoid interaction

1999

In the 1970s ecological research detected chaos and other forms of complex dynamics in simple population dynamics models, initiating a new research tradition in ecology. However, the investigations of complex population dynamics have mainly concentrated on single populations and not on higher dimensional ecological systems. Here we report a detailed study of the complicated dynamics occurring in a basic discrete-time model of host-parasitoid interaction. The complexities include (a) non-unique dynamics, meaning that several attractors coexist, (b) basins of attraction (defined as the set of the initial conditions leading to a certain type of an attractor) with fractal properties (pattern of…

0106 biological sciencesStatistics and ProbabilityEcology (disciplines)PopulationChaoticBiologyBifurcation diagram010603 evolutionary biology01 natural sciencesGeneral Biochemistry Genetics and Molecular Biologylaw.invention03 medical and health sciencesFractalControl theorylawIntermittencyAttractorQuantitative Biology::Populations and EvolutionStatistical physicseducation030304 developmental biology0303 health scienceseducation.field_of_studyGeneral Immunology and MicrobiologyApplied MathematicsGeneral MedicineComplex dynamicsModeling and SimulationGeneral Agricultural and Biological SciencesJournal of theoretical biology
researchProduct

Effects of patch number and dispersal patterns on population dynamics and synchrony.

2000

In this paper, we examine the effects of patch number and different dispersal patterns on dynamics of local populations and on the level of synchrony between them. Local population renewal is governed by the Ricker model and we also consider asymmetrical dispersal as well as the presence of environmental heterogeneity. Our results show that both population dynamics and the level of synchrony differ markedly between two and a larger number of local populations. For two patches different dispersal rules give very versatile dynamics. However, for a larger number of local populations the dynamics are similar irrespective of the dispersal rule. For example, for the parameter values yielding stab…

0106 biological sciencesStatistics and ProbabilityPopulationPopulation DynamicsBiology010603 evolutionary biology01 natural sciencesPopulation densityModels BiologicalGeneral Biochemistry Genetics and Molecular Biology03 medical and health sciencesQuantitative Biology::Populations and EvolutionAnimalsLocal populationPopulation dynamicseducation030304 developmental biologyPopulation Density0303 health scienceseducation.field_of_studyGeneral Immunology and MicrobiologyEcologyApplied MathematicsHigh intensityDynamics (mechanics)General MedicineRicker modelModeling and SimulationBiological dispersalGeneral Agricultural and Biological SciencesJournal of theoretical biology
researchProduct

Non-linear biological responses to disturbance: consequences on population dynamics

2003

Abstract We assessed how non-linear biological responses to environmental noise, or “noise filtering”, impact the spectra of density-dependent population dynamics, and the correlation between noise and population dynamics. The noise was assumed to affect population growth rate in a discrete-time population model by Hassell [J. Anim. Ecol. 44 (1975) 283–295] where the population growth rate was linked to the environment with an optimum type filter. When compared to unfiltered noise, the filtered noise can distort the stationary distribution of population values. The optimum type filter can make cyclic population dynamics more regular and low population values can become more frequent or rare…

0106 biological scienceseducation.field_of_study010604 marine biology & hydrobiologyEcological ModelingPopulation sizePopulationFilter (signal processing)010603 evolutionary biology01 natural sciencesPopulation densityDensity dependencePopulation modelStatisticsQuantitative Biology::Populations and EvolutionPopulation growtheducationEnvironmental noiseMathematicsEcological Modelling
researchProduct

A generalization of Kingman's model of selection and mutation and the Lenski experiment.

2017

Kingman’s model of selection and mutation studies the limit type value distribution in an asexual population of discrete generations and infinite size undergoing selection and mutation. This paper generalizes the model to analyze the long-term evolution of Escherichia. coli in Lenski experiment. Weak assumptions for fitness functions are proposed and the mutation mechanism is the same as in Kingman’s model. General macroscopic epistasis are designable through fitness functions. Convergence to the unique limit type distribution is obtained.

0301 basic medicineStatistics and ProbabilityGeneralizationPopulationBiology01 natural sciencesModels BiologicalGeneral Biochemistry Genetics and Molecular Biology010104 statistics & probability03 medical and health sciencesStatisticsEscherichia coliApplied mathematicsQuantitative Biology::Populations and EvolutionLimit (mathematics)0101 mathematicsSelection GeneticeducationSelection (genetic algorithm)education.field_of_studyFitness functionGeneral Immunology and MicrobiologyApplied MathematicsGeneral MedicineQuantitative Biology::GenomicsBiological Evolution030104 developmental biologyDistribution (mathematics)Modeling and SimulationMutation (genetic algorithm)MutationEpistasisGeneral Agricultural and Biological SciencesMathematical biosciences
researchProduct

Evolutionary distances corrected for purifying selection and ancestral polymorphisms.

2019

Abstract Evolutionary distance formulas that take into account effects due to ancestral polymorphisms and purifying selection are obtained on the basis of the full solution of Jukes–Cantor and Kimura DNA substitution models. In the case of purifying selection two different methods are developed. It is shown that avoiding the dimensional reduction implicitly carried out in the conventional model solving is instrumental to incorporate the quoted effects into the formalism. The problem of estimating the numerical values of the model parameters, as well as those of the correction terms, is not addressed.

0301 basic medicineStatistics and ProbabilityTime FactorsADNModel parametersGeneral Biochemistry Genetics and Molecular Biology03 medical and health sciencesNegative selection0302 clinical medicineQuantitative Biology::Populations and EvolutionStatistical physicsSelection GeneticMolecular clockPhylogenyMathematicsPolymorphism GeneticGeneral Immunology and MicrobiologyApplied MathematicsGeneral MedicineModels biològicsQuantitative Biology::GenomicsBiological EvolutionFormalism (philosophy of mathematics)030104 developmental biologyDimensional reductionModeling and SimulationMutationGeneral Agricultural and Biological Sciences030217 neurology & neurosurgeryEvolució (Biologia)Journal of theoretical biology
researchProduct