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45 results for “Stochastic dynamics”
SUPPORTING INFORMATION FOR: Stochastic dynamic mass spectrometric 3D structural analysis of caffeine metabolites
<p>Supporting information for the entitled contribution.</p><p>It contains:</p><p>Static quantum chemical and high accuracy molecular dynamics computational data on protomers, tautomers, zwitterions, and isotopomers of caffeine (CAFF), paraxanthine (PARAXAN), theobromine (THEOBR), theophylline (THEOPH), and guanine (GUA), uric acid (UA), and xantine (XAN), as well as their derivatives.</p><p>The content includes data on characteristic parent and product ions of the analytes in ion mobility spectrometric and mass spectrometric experimental conditions. Tautomers, charge transfer processes, and intramolecular rearrangement; if any, are accounted for considering. </p><p>Molecular mechanics/molecular dynamics data are shown as *.txt files. </p><p>High accuracy molecular dynamics includes adiabatic computations using Born-Oppenheimer approach.</p><p>High accuracy static ground state and transition state computations use M062X/SDD level of theory. </p><p>Figures in color, illustrating the entitled contribution shown as *.pdf files.</p><p>The experimental ion mobility spectrometry and mass spectrometry data are according to reference [1].</p><p>[1] H. Sepman, A. Kruve, S. Tshepelevitsh, H. Hupatz, Experimental IMS and MS/MS data of caffeine metabolites (2022). Zenodo, [https://doi.org/10.5281/zenodo.6637393][ https://zenodo.org/record/6637393] (Accessible for 04.04.2022.)</p><p>They have been used and processed via the following software:</p><p>[2] ProteoWizard 3.0.11565.0 (2017) [https://proteowizard.sourceforge.io/download.html];</p><p>[3] mMass 5.0.0 [http://www.mmass.org/download/old.php];</p><p>[4] AMDIS 2.71 (2012) software [https://chemdata.nist.gov/mass-spc/amdis/downloads/AMDIS_Installer-17.zip]; and</p><p>[5] NIST Search Software 2.0 [https://chemdata.nist.gov/dokuwiki/lib/exe/fetch.php?media=chemdata:nist17:nist17demo.zip], respectively.</p><p> </p><p> </p>
A basic community dynamics experiment: Disentangling deterministic and stochastic processes in structuring ecological communities
<p>Community dynamics are governed by two opposed processes: species sorting, which produces deterministic dynamics leading to an equilibrium state, and ecological drift, which produces stochastic dynamics. Despite a great deal of theoretical and empirical work aiming to demonstrate the predominance of one or the other of these processes, the importance of drift in structuring communities and maintaining species diversity remains contested. Here we present the results of a basic community dynamics experiment using floating aquatic plants, designed to measure the relative contributions of species sorting and ecological drift to community change over about a dozen generations. We found that species sorting became overwhelmingly dominant as the experiment progressed, and directed communities towards a stable equilibrium state maintained by negative frequency-dependent selection. The dynamics of any particular species depended on how far its initial frequency was from its equilibrium frequency, however, and consequently the balance of sorting and drift varied among species.</p>
Laser Ablation Inductively Coupled Plasma Mass Spectrometric Quantification of Isotope Trace Elements in Human Carcinoma Tissue - Stochastic Dynamics and Theoretical Analysis (SUPPORTING INFORMATION)
<p>Supporting information file of publication [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4334866]. </p>
First-passage probability estimation of high-dimensional nonlinear stochastic dynamic systems by a fractional moments-based mixture distribution approach
<p>First-passage probability estimation of high-dimensional nonlinear stochastic dynamic systems is a significant task to be solved in many science and engineering fields, but remains still an open challenge. The present paper develops a novel approach, termed ‘fractional moments-based mixture distribution’, to address such challenge. This approach is implemented by capturing the extreme value distribution (EVD) of the system response with the concepts of fractional<br> moment and mixture distribution. In our context, the fractional moment itself is by definition a high-dimensional integral with a complicated integrand. To efficiently compute the fractional moments, a parallel adaptive sampling scheme that allows for sample size extension is developed using the refined Latinized stratified sampling (RLSS). In this manner, both variance reduction and parallel computing are possible for evaluating the fractional moments. From the knowledge<br> of low-order fractional moments, the EVD of interest is then expected to be reconstructed. Based on introducing an extended inverse Gaussian distribution and a log extended skew-normal distribution, one flexible mixture distribution model is proposed, where its fractional moments are derived in analytic form. By fitting a set of fractional moments, the EVD can be recovered via the proposed mixture model. Accordingly, the first-passage probabilities under different<br> thresholds can be obtained from the recovered EVD straightforwardly. The performance of the proposed method is verified by three examples consisting of two test examples and one engineering problem.</p>
Data and code for: Stochastic bacterial population dynamics restrict the establishment of antibiotic resistance from single cells
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A basic community dynamics experiment: Disentangling deterministic and stochastic processes in structuring ecological communities
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Data from: Stochastic population dynamics and life-history variation in marine fish species
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Data from: Stochasticity and infectious disease dynamics: density and weather effects on a fungal insect pathogen
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Data from: Within-host stochastic emergence dynamics of immune-escape mutants
Predicting the emergence of new pathogenic strains is a key goal of evolutionary epidemiology. However, the majority of existing studies have focussed on emergence at the population level, and not within a host. In particular, the coexistence of pre-existing and mutated strains triggers a heightened immune response due to the larger total pathogen population; this feedback can smother mutated strains before they reach an ample size and establish. Here, we extend previous work for measuring emergence probabilities in non-equilibrium populations, to within-host models of acute infections. We create a mathematical model to investigate the emergence probability of a fitter strain if it mutates from a self-limiting strain that is guaranteed to go extinct in the long-term. We show that ongoing immune cell proliferation during the initial stages of infection causes a drastic reduction in the probability of emergence of mutated strains; we further outline how this effect can be accurately measured. Further analysis of the model shows that, in the short-term, mutant strains that enlarge their replication rate due to evolving an increased growth rate are more favoured than strains that suffer a lower immune-mediated death rate ('immune tolerance'), as the latter does not completely evade ongoing immune proliferation due to inter-parasitic competition. We end by discussing the model in relation to within-host evolution of human pathogens (including HIV, hepatitis C virus, and cancer), and how ongoing immune growth can affect their evolutionary dynamics.
Computer codes (in Python) for 'The reproduction number and its probability distribution for stochastic viral dynamics'
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Data and climate variable selection from: Effects of density, species interactions and environmental stochasticity on the dynamics of British bird communities
<p>Our knowledge of the factors affecting species abundances is mainly based on time-series analyses of a few well-studied species at single or few localities, but we know little about whether results from such analyses can be extrapolated to the community level. We apply a Joint Species Distribution Model to long-term time-series data on British bird communities to examine the relative contribution of intra- and interspecific density dependence at different spatial scales, as well as the influence of environmental stochasticity, to spatio-temporal interspecific variation in abundance. Intraspecific density dependence has the major structuring effect on these bird communities. In addition, environmental fluctuations affect spatiotemporal differences in abundance. In contrast, species interactions had a minor impact on variation in abundance. Thus, important drivers of single-species dynamics are also strongly affecting dynamics of communities in time and space.</p>
Data from: Contrasting effects of spatial heterogeneity and environmental stochasticity on population dynamics of a perennial wildflower
Understanding how variation in growth, survival and reproduction affect population dynamics is a fundamental question in ecology. Although the effects of among-year variation (environmental stochasticity) are well understood, the effects of among-site variation (spatial heterogeneity) are less clearly defined. I evaluated the effects of spatial and temporal variation on the population dynamics of Pulsatilla patens, pasqueflower, a perennial prairie forb. I conducted a 10-year demographic monitoring study, and quantified vital rate variation among sites and years using generalized linear models. I incorporated vital rate functions using this variation into integral projection models for stochastic and spatially heterogeneous environments. I also explored the effects of temporal and spatial autocorrelation, by exploring model predictions over the range of possible values for temporal autocorrelation and local seed dispersal. Vital rates varied more among years than among sites. However, environmental stochasticity and spatial heterogeneity had similar magnitude effects on population dynamics. These effects were also qualitatively different: environmental stochasticity reduced population growth rates relative to the average, whereas spatial heterogeneity increased population growth rates. Spatial autocorrelation and negative temporal autocorrelation led to higher population growth rates, although environmental stochasticity still reduced growth rates for all autocorrelation values, and spatial heterogeneity increased growth rates for all autocorrelation values. Some form of autocorrelation would be necessary for model projections to match observed population trends. Synthesis. Spatial heterogeneity is as important as environmental stochasticity for population dynamics, but it is much less often incorporated into population projection models. This study points to a number of interesting avenues for future research into the roles of spatial heterogeneity and spatiotemporal variation for long-term population dynamics.
Data from: Stochastic dynamics of three competing clones: conditions and times for invasion, coexistence and fixation
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Data from: Contrasting effects of spatial heterogeneity and environmental stochasticity on population dynamics of a perennial wildflower
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Data and climate variable selection from: Effects of density, species interactions and environmental stochasticity on the dynamics of British bird communities
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Data from: Within-host stochastic emergence dynamics of immune-escape mutants
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Transition state dynamics during a stochastic fate choice
GEO Series GSE128974. Dictyostelium discoideum. 123 samples. Type: Expression profiling by high throughput sequencing.
Stochastic models of nucleosome dynamics reveal regulatory rules of stimulus-induced epigenome remodeling
GEO Series GSE156385. Mus musculus. 4 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Stochastic Sampling of Operator Growth Dynamics - Monte Carlo Data
<p>Monte Carlo Data for preprint https://arxiv.org/abs/2401.06215 . The paper has been accepted to Physical Review B.</p> <p>DOI - https://doi.org/10.1103/PhysRevB.110.155135</p>
Mass spectrometric diffusion parameters and 3D structural analysis of oligomeric associates of glycylhomopenta– and glycylhomohexapeptide and their complexes of silver(I) ion – a stochastic dynamics approach - mass spectrometric dataset
<p>Experimental mass spectrometric dataset (in multiplication) of Ag<sup>I</sup>-complexes of glycyl-containing oligopeptides under ESI(+)-conditions.</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
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