scholarly journals A delay-deterministic model for inferring fitness effects from time-resolved genome sequence data

2017 ◽  
Author(s):  
Nuno R. Nené ◽  
Alistair S. Dunham ◽  
Christopher J. R. Illingworth
Keyword(s):  
Finite Population ◽  
Deterministic Model ◽  
Sequence Data ◽  
Evolutionary System ◽  
Deterministic Models ◽  
Time Resolved ◽  
General Application ◽  
Fitness Effects ◽  
Alternative Approach ◽  
Complex Models

ABSTRACTA common challenge arising from the observation of an evolutionary system over time is to infer the magnitude of selection acting upon a specific genetic variant, or variants, within the population. The inference of selection may be confounded by the effects of genetic drift in a system, leading to the development of inference procedures to account for these effects. However, recent work has suggested that deterministic models of evolution may be effective in capturing the effects of selection even under complex models of demography, suggesting the more general application of deterministic approaches to inference. Responding to this literature, we here note a case in which a deterministic model of evolution may give highly misleading inferences, resulting from the non-deterministic properties of mutation in a finite population. We propose an alternative approach which corrects for this error, which we denote the delay-deterministic model. Applying our model to a simple evolutionary system we demonstrate its performance in quantifying the extent of selection acting within that system. We further consider the application of our model to sequence data from an evolutionary experiment. We outline scenarios in which our model may produce improved results for the inference of selection, noting that such situations can be easily identified via the use of a regular deterministic model.

scholarly journals Inferring Fitness Effects from Time-Resolved Sequence Data with a Delay-Deterministic Model

Genetics ◽  
2018 ◽  
Vol 209 (1) ◽  
pp. 255-264 ◽  
Author(s):  
Nuno R. Nené ◽  
Alistair S. Dunham ◽  
Christopher J. R. Illingworth
Keyword(s):  
Deterministic Model ◽  
Sequence Data ◽  
Time Resolved ◽  
Fitness Effects

scholarly journals Origin of the European avian-like swine influenza viruses

2014 ◽  
Vol 95 (11) ◽  
pp. 2372-2376 ◽  
Author(s):  
Andi Krumbholz ◽  
Jeannette Lange ◽  
Andreas Sauerbrei ◽  
Marco Groth ◽  
Matthias Platzer ◽  
...  
Keyword(s):  
Avian Influenza ◽  
Phylogenetic Trees ◽  
Sequence Data ◽  
Swine Influenza ◽  
H1n1 Influenza ◽  
Molecular Data ◽  
Influenza Viruses ◽  
Time Resolved ◽  
Genotype Constellation ◽  
Tree Inference

The avian-like swine influenza viruses emerged in 1979 in Belgium and Germany. Thereafter, they spread through many European swine-producing countries, replaced the circulating classical swine H1N1 influenza viruses, and became endemic. Serological and subsequent molecular data indicated an avian source, but details remained obscure due to a lack of relevant avian influenza virus sequence data. Here, the origin of the European avian-like swine influenza viruses was analysed using a collection of 16 European swine H1N1 influenza viruses sampled in 1979–1981 in Germany, the Netherlands, Belgium, Italy and France, as well as several contemporaneous avian influenza viruses of various serotypes. The phylogenetic trees suggested a triple reassortant with a unique genotype constellation. Time-resolved maximum clade credibility trees indicated times to the most recent common ancestors of 34–46 years (before 2008) depending on the RNA segment and the method of tree inference.

scholarly journals Determinism

2021 ◽  
Vol 20 (5) ◽  
pp. 1-34
Author(s):  
Edward A. Lee
Keyword(s):  
Quantum Physics ◽  
Deterministic Model ◽  
Physical World ◽  
Deterministic Models ◽  
Newtonian Physics ◽  
Physical Systems ◽  
Newton’S Laws ◽  
And Behavior

This article is about deterministic models, what they are, why they are useful, and what their limitations are. First, the article emphasizes that determinism is a property of models, not of physical systems. Whether a model is deterministic or not depends on how one defines the inputs and behavior of the model. To define behavior, one has to define an observer. The article compares and contrasts two classes of ways to define an observer, one based on the notion of “state” and another that more flexibly defines the observables. The notion of “state” is shown to be problematic and lead to nondeterminism that is avoided when the observables are defined differently. The article examines determinism in models of the physical world. In what may surprise many readers, it shows that Newtonian physics admits nondeterminism and that quantum physics may be interpreted as a deterministic model. Moreover, it shows that both relativity and quantum physics undermine the notion of “state” and therefore require more flexible ways of defining observables. Finally, the article reviews results showing that sufficiently rich sets of deterministic models are incomplete. Specifically, nondeterminism is inescapable in any system of models rich enough to encompass Newton’s laws.

Mapping of digested and undigested random amplified microsatellite polymorphisms in barley

Genome ◽  
1995 ◽  
Vol 38 (5) ◽  
pp. 991-998 ◽  
Author(s):  
Jörg Becker ◽  
Manfred Heun
Keyword(s):  
Simple Sequence Repeats ◽  
Dna Markers ◽  
Simple Sequence Repeat ◽  
Sequence Data ◽  
Linkage Maps ◽  
Sequence Repeat ◽  
Rflp Map ◽  
Alternative Approach ◽  
Microsatellite Mapping ◽  
Simple Sequence

The broad use of microsatellites as a tool for constructing linkage maps in plants has been limited by the need for sequence data to detect the underlying simple sequence repeats. Therefore, random amplified microsatellite polymorphisms (RAMPs) were studied as an alternative approach for barley mapping. Labelled (GA)n simple sequence repeat primers were combined with RAPD primers of different length and sequence to generate RAMPs. To get additional polymorphisms (called dRAMPs), the obtained products were also analysed after digestion with MseI. There were 0–11 polymorphisms found per primer combination. Sixty RAMPs/dRAMPs identifying 40 new loci were mapped onto a barley RFLP map. The new DNA markers are found on all chromosomes and they increased the length of the barley map by 174 cM to a total of 1270 cM. Interestingly, the RAMPs/dRAMPs caused stretching effects in genome areas where stretching was also observed for AFLPs.Key words: barley, microsatellite, mapping, RAMP, RFLP.

scholarly journals Insights into the deterministic skill of air quality ensembles from the analysis of AQMEII data

2016 ◽  
Vol 16 (24) ◽  
pp. 15629-15652 ◽  
Author(s):  
Ioannis Kioutsioukis ◽  
Ulas Im ◽  
Efisio Solazzo ◽  
Roberto Bianconi ◽  
Alba Badia ◽  
...  
Keyword(s):  
Air Quality ◽  
Deterministic Model ◽  
Ensemble Methods ◽  
Ground Level ◽  
Chemical Mechanism ◽  
Second Phase ◽  
Air Quality Model ◽  
Quality Model ◽  
Deterministic Models ◽  
Ensemble Mean

Abstract. Simulations from chemical weather models are subject to uncertainties in the input data (e.g. emission inventory, initial and boundary conditions) as well as those intrinsic to the model (e.g. physical parameterization, chemical mechanism). Multi-model ensembles can improve the forecast skill, provided that certain mathematical conditions are fulfilled. In this work, four ensemble methods were applied to two different datasets, and their performance was compared for ozone (O3), nitrogen dioxide (NO2) and particulate matter (PM10). Apart from the unconditional ensemble average, the approach behind the other three methods relies on adding optimum weights to members or constraining the ensemble to those members that meet certain conditions in time or frequency domain. The two different datasets were created for the first and second phase of the Air Quality Model Evaluation International Initiative (AQMEII). The methods are evaluated against ground level observations collected from the EMEP (European Monitoring and Evaluation Programme) and AirBase databases. The goal of the study is to quantify to what extent we can extract predictable signals from an ensemble with superior skill over the single models and the ensemble mean. Verification statistics show that the deterministic models simulate better O3 than NO2 and PM10, linked to different levels of complexity in the represented processes. The unconditional ensemble mean achieves higher skill compared to each station's best deterministic model at no more than 60 % of the sites, indicating a combination of members with unbalanced skill difference and error dependence for the rest. The promotion of the right amount of accuracy and diversity within the ensemble results in an average additional skill of up to 31 % compared to using the full ensemble in an unconditional way. The skill improvements were higher for O3 and lower for PM10, associated with the extent of potential changes in the joint distribution of accuracy and diversity in the ensembles. The skill enhancement was superior using the weighting scheme, but the training period required to acquire representative weights was longer compared to the sub-selecting schemes. Further development of the method is discussed in the conclusion.

scholarly journals Determining a reasonable range of relative numerical tolerance values for simulating deterministic models of biochemical reactions

2018 ◽  
Author(s):  
Ming Yang ◽  
Louis Z. Yang
Keyword(s):  
Uncertainty Principle ◽  
Deterministic Model ◽  
Biochemical Reaction ◽  
Biochemical Reactions ◽  
Deterministic Models ◽  
Modeling Effort ◽  
Reasonable Range ◽  
Simulation Results

ABSTRACTWhat values of relative numerical tolerance should be chosen in simulation of a deterministic model of a biochemical reaction is unclear, which impairs the modeling effort since the simulation outcomes of a model may depend on the relative numerical tolerance values. In an attempt to provide a guideline to selecting appropriate numerical tolerance values in simulation of in vivo biochemical reactions, reasonable numerical tolerance values were estimated based on the uncertainty principle and assumptions of related cellular parameters. The calculations indicate that relative numerical tolerance values can be reasonably set at or around 10−4 for the concentrations expressed in ng/L. This work also suggests that further reducing relative numerical values may result in erroneous simulation results.

scholarly journals Fitness estimation for viral variants in the context of cellular coinfection

2021 ◽  
Author(s):  
Huisheng Zhu ◽  
Brent E Allman ◽  
Katia Koelle
Keyword(s):  
Evolutionary Dynamics ◽  
Sequence Data ◽  
Population Level ◽  
Viral Fitness ◽  
Fitness Effects ◽  
Fitness Advantage ◽  
Viral Adaptation ◽  
Zoonotic Viruses ◽  
Frequency Changes

AbstractAnimal models are frequently used to characterize the within-host dynamics of emerging zoonotic viruses. More recent studies have also deep-sequenced longitudinal viral samples originating from experimental challenges to gain a better understanding of how these viruses may evolve in vivo and between transmission events. These studies have often identified nucleotide variants that can replicate more efficiently within hosts and also transmit more effectively between hosts. Quantifying the degree to which a mutation impacts viral fitness within a host can improve identification of variants that are of particular epidemiological concern and our ability to anticipate viral adaptation at the population level. While methods have been developed to quantify the fitness effects of mutations using observed changes in allele frequencies over the course of a host’s infection, none of the existing methods account for the possibility of cellular coinfection. Here, we develop mathematical models to project variant allele frequency changes in the context of cellular coinfection and, further, integrate these models with statistical inference approaches to demonstrate how variant fitness can be estimated alongside cellular multiplicity of infection. We apply our approaches to empirical longitudinally-sampled H5N1 sequence data from ferrets. Our results indicate that previous studies may have significantly underestimated the within-host fitness advantage of viral variants. These findings underscore the importance of considering the process of cellular coinfection when studying within-host viral evolutionary dynamics.

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