Find research datasets worth reusing

U-helix:drug Complex Molecular Dynamics Trajectories

Molecular dynamics trajectories for U-helix RNA-ligand complexes. Described in the following paper: Targeting RNA Structure to Inhibit Editing in Trypanosomes in the International Journal of Molecular Sciences, 2023, volume 24.

Data set for "Membrane potential dynamics of excitatory and inhibitory neurons in mouse barrel cortex during active whisker sensing"

Data set for: Kiritani T, Pala A, Gasselin C, Crochet S, Petersen CCH (2023) Membrane potential dynamics of excitatory and inhibitory neurons in mouse barrel cortex during active whisker sensing. PLOS ONE 18: e0287174. doi: 10.1371/journal.pone.0287174 There are 2 files in this upload: 1. The file named "2023_Kiritani_PLOSONE.pdf" is the Open Access pdf of the online publication in PLOS ONE. 2. The file named "Kiritani_data_code.zip" (~5 GB) is a zipped version of a folder "Kiritani_data_code" (~5 GB), which contains the data analysed in the study along with the Matlab codes used to generate the published figures. To access the data and codes, first unzip the file. You need to install the Matlab 'Signal Processing' and 'Curve Fitting' Toolboxes. In Matlab, add the path of the folder 'Kiritani_data_code' and all subfolders. Directly from this folder, you should first run the codes in the folder 'Data_Analysis_Codes', sequentially executing 'Analysis_1.m' through to 'Analysis_9.m'. Note, execution of 'Analysis_9.m' can take a long time (~1 hour on a good desktop PC). You can then run the codes in the folder 'Figure_Plotting_Codes' to generate the figures published in the journal article. In the folder 'Data', you can also find a DataViewer to visualise the data sets, which you can run by executing 'DataViewer.m' directly from the subfolder ‘Data’.

Data from: Additive genetic and environmental variation interact to shape the dynamics of seasonal migration in a wild bird population

Dissecting joint micro-evolutionary and plastic responses to environmental perturbations requires quantifying interacting components of genetic and environmental variation underlying expression of key traits. This ambition is particularly challenging for phenotypically discrete traits where multiscale decompositions are required to reveal non-linear transformations of underlying genetic and environmental variation into phenotypic variation, and when effects must be estimated from incomplete field observations. We devised a joint multistate capture-recapture and quantitative genetic animal model and fitted this model to full-annual-cycle resighting data from partially-migratory European shags (Gulosus aristotelis) to estimate key components of genetic, environmental and phenotypic variance in the ecologically critical discrete trait of seasonal migration versus residence. We demonstrate non-negligible additive genetic variance in latent liability for migration, resulting in detectable micro-evolutionary responses following two episodes of strong survival selection. Further, liability-scale additive genetic effects interacted with substantial permanent individual and temporary environmental effects to generate complex non-additive effects on expressed phenotypes, causing substantial intrinsic gene-by-environment interaction variance on the phenotypic scale. Our analyses therefore reveal how temporal dynamics of partial seasonal migration arise from combinations of instantaneous micro-evolution and within-individual phenotypic consistency, and highlight how intrinsic phenotypic plasticity could expose genetic variation underlying discrete traits to complex forms of selection.

Ecological interactions driving population dynamics of two tick-borne pathogens, Borrelia burgdorferi and Babesia microti

Borrelia burgdorferi (Bb) and Babesia microti (Bm) are vector-borne zoonotic pathogens commonly found co-circulating in Ixodes scapularis and Peromyscus leucopus populations. The restricted distribution and lower prevalence of Bm has been historically attributed to lower host-to-tick transmission efficiency and limited host ranges. We hypothesized that prevalence patterns are driven by coinfection dynamics and vertical transmission. We use a multi-year, multiple-location, longitudinal dataset with mathematical modelling to elucidate coinfection dynamics between Bb and Bm in natural populations of P. leucopus, the most competent reservoir host for both pathogens in the eastern USA. Our analysis indicates that, in the absence of vertical transmission, Bb is viable at lower tick numbers than Bm. However, with vertical transmission, Bm is viable at lower tick numbers than Bb. Vertical transmission has a particularly strong effect on Bm prevalence early in the active season while coinfection has an increasing role during the nymphal peak. Our analyses indicate that coinfection processes, such as facilitation of Bm infection by Bb, have relatively little influence on the persistence of either parasite. We suggest future work examines the sensitivity of Bm vertical transmission and other key processes to local environmental conditions to inform surveillance and control of tick-borne pathogens.

Data from: Evaluating the importance of individual heterogeneity in reproduction to Weddell seal population dynamics using integral projection models

<ol> <li>Identifying and accounting for unobserved individual heterogeneity in vital rates in demographic models is important for estimating population-level vital rates and identifying diverse life-history strategies, but much less is known about how this individual heterogeneity influences population dynamics.</li> <li>We aimed to understand how the distribution of individual heterogeneity in reproductive and survival rates influenced population dynamics using vital rates from a Weddell seal population by altering the distribution of individual heterogeneity in reproduction, which also altered the distribution of individual survival rates through the incorporation of our estimate of the correlation between the two rates and assessing resulting changes in population growth.</li> <li>We constructed an integral projection model (IPM) structured by age and reproductive state using estimates of vital rates for a long-lived mammal that has recently been shown to exhibit large individual heterogeneity in reproduction. Using output from the IPM, we evaluated how population dynamics changed with different underlying distributions of unobserved individual heterogeneity in reproduction.</li> <li>Results indicate that the changes to the underlying distribution of individual heterogeneity in reproduction cause very small changes in the population growth rate and other population metrics. The largest difference in the estimated population growth rate resulting from changes to the underlying distribution of individual heterogeneity was less than 1%.</li> <li>Our work highlights the differing importance of individual heterogeneity at the population level compared to the individual level. Although individual heterogeneity in reproduction may result in large differences in the lifetime fitness of individuals, changing the proportion of above- or below-average breeders in the population results in much smaller differences in annual population growth rate. For a long-lived mammal with stable and high adult-survival that gives birth to a single offspring, individual heterogeneity in reproduction has a limited effect on population dynamics. We posit that the limited effect of individual heterogeneity on population dynamics may be due to canalization of life-history traits.</li> </ol>

Dynamics-based characterisation and classification of biodiversity indicators

Various biodiversity indicators, such as species richness, total abundance, and species diversity indices, have been developed to capture the state of ecological communities over space and time. As biodiversity is a multifaceted concept, it is important to understand the dimension of biodiversity reflected by each indicator for successful conservation and management. Here we utilised the responsiveness of biodiversity indicators' dynamics to environmental changes (i.e. environmental responsiveness) as a signature of the dimension of biodiversity. We present a method for characterising and classifying biodiversity indicators according to environmental responsiveness and apply the methodology to monitoring data for a marine fish community under intermittent anthropogenic warm water discharge. Our analysis showed that ten biodiversity indicators can be classified into three super-groups based on the dimension of biodiversity that is reflected. Group I (species richness and community mean of centre of distribution latitude (cCOD)) showed the greatest robustness to temperature changes; Group II (species diversity and total abundance) showed an abrupt change in the middle of the monitoring period, presumably due to a change in temperature; Group III (species evenness) exhibited the highest sensitivity to environmental changes, including temperature. These results had several ecological implications. First, the responsiveness of species diversity and species evenness to temperature changes might be related to changes in the species abundance distribution. Second, the similar environmental responsiveness of species richness and cCOD implies that fish migration from lower latitudes is a major driver of species compositional changes. The study methodology may be useful in selecting appropriate indicators for efficient biodiversity monitoring.

opencc-by-4.0Mar 2023View details →

Data for publication "Measuring the environment of a Cs qubit with dynamical decoupling sequences"

Data sets as plotted in the preprint "Measuring the environment of a Cs qubit with dynamical decoupling sequences" are uploaded. The zip file "data" contains a folder for each figure in the preprint (named after the figure). Each folder contains the data for all graphs in the respective figure.

Data for: Coupling dynamic energy budget and population dynamic models to inform stock enhancement in fisheries management

Extensive applications of fishery stock enhancement worldwide bring up broad concerns about its negative effects, creating a pivotal need for science-based assessment and planning of enhancement strategies. However, the lack of mechanistic understanding of enhanced population dynamics, particularly the density-dependent processes, leads to compromise in model development and limits the capacity in predicting enhancement effects. Here, we developed an individual-based model based on dynamic energy budget theory and full life history processes, to understand the mechanism of density dependence in population dynamics that emerge from individual-level processes. We demonstrated the utility of the model framework by applying it to an extensively enhanced species, Chinese prawn (Fenneropenaeus chinensis, Penaeidae). The model could yield projections reflecting the observed trajectory of population biomass and yields. The model also delineated the key effects of density dependence on the vital rates of growth, fecundity, and starvation mortality. Regarding the manifold effects of stock enhancement, we demonstrated a dampened shape in population biomass and yields with increasing magnitude of enhancement, and trade-offs between the ecological and economic objectives, i.e., pursuing high benefit might compromise the wild population without proper management. Furthermore, we illustrated the possibility of combining stock enhancement and harvest regulation in promoting population recovery while maintaining fisheries yields. We highlight the potential of the proposed model for understanding density dependence in enhancement program, and for designing integrated management strategies. The approach developed herein may serve as a general approach to assess the population dynamics in stock enhancement and inform enhancement management.

Genomic epidemiology unveils the dynamics and spatial corridor behind the Yellow Fever virus outbreak in Southern Brazil

Despite the considerable morbidity and mortality of yellow fever virus (YFV) infections in Brazil our understanding of disease outbreaks is hampered by limited viral genomic data. Determining the timing and spatial corridors of YFV spread, as well as the geographic hotspots that link the endemic north of the country with epidemic extra-Amazonian regions, are central to predicting and preventing future outbreak and epidemics. Here, we tracked the recent spread of the virus by integrating genome sequences with both epidemiological and vector data. Through a combination of phylogenetic and epidemiological models we reconstructed the recent transmission history of YFV within different epidemic seasons in Brazil. A suitability index based on the highly domesticated Aedes aegypti was able to capture the seasonality of reported human infections. Spatial modelling revealed spatial hotspots with both past reporting and low vaccination coverage, which coincided with many of the largest urban centres in the Southeast. Phylodynamic analysis unravelled the circulation of three distinct YFV lineages, and provided proof of the directionality of a known spatial corridor of viral spread that connects the endemic North with the extra-Amazonian basin. This study illustrates that genomics linked with eco-epidemiology in a One Health framework can provide new insights into the landscape of YFV transmission, augmenting traditional approaches to infectious disease surveillance and control.

Data repository for Pore Pressure Drop during Dynamic Rupture and Conditions for Dilatancy Hardening

Simulation data to accompany publication Pore pressure drop during dynamic rupture and conditions for dilatancy hardening, submitted to Journal of Geophysical Research: Solid Earth. See Readme.txt for content of data files. The data were generated by 'GrandFrix' software and postprocessed by scripts written MATLAB  – see Related identifiers.

opencc-by-4.0Jan 2023View details →

Shear viscosity coefficient of acqueous glycerol from non-equilibrium Molecular Dynamics simulations

This dataset contains the results of non-equilibrium atomistic Molecular Dynamics simulations of water-glycerol liquid mixtures, at various relative concentrations. The goal of the simulations is to quantify the shear viscosity coefficient of said mixtures using the periodic perturbation technique [1].  The pattern "Glycerol***" refers to the mass fraction of glycerol ("000": pure water, "100": pure glycerol). Each folder contains three sets of simulations, with different perturbation force parameters ("Em*"), where configuration files necessary to reproduce molecular simulations simulations are provided. Maps of density and velocity field are in "Em*"->"Flow". A small self-contained Python script to fit the velocity fields to a periodic cosine perturbation is provided (fit-periodic.py). Alternatively, viscosity can be obtained from energy outputs by running: <pre><code>gmx energy -f ener.edr</code></pre> and selecting "1/Viscosity". Simulations are performed with Gromacs. We refer to the code documentation for further information (<a href="https://manual.gromacs.org/">https://manual.gromacs.org/</a>). References: [1] B. Hess, Determining the shear viscosity of model liquids from molecular dynamics simulations, J. Chem. Phys. 116, 209–217 (2002) <a href="https://doi.org/10.1063/1.1421362">https://doi.org/10.1063/1.1421362</a>

opencc-by-4.0Jan 2023View details →

Shear viscosity coefficient of acqueous glycerol from equilibrium Molecular Dynamics simulations

This dataset contains the results of equilibrium atomistic Molecular Dynamics simulations of water-glycerol liquid mixtures, at various relative concentrations. The goal of the simulations is to quantify the shear viscosity coefficient of said mixtures using linear response theory (Einstein relations) [1]. The post-processing of simulation results is inspired by the method of Zhang et al. [2]. The pattern "Glycerol***" refers to the mass fraction of glycerol, being "000" pure water (0%) and "100" pure glycerol (100%). Zip folders contain <ul> <li>Expected value and integral of the square of the off-diagonal components of the pressure gradient ("EnergyOutputs")</li> <li>Initial configurations used to start the ensemble of replicas from which viscosity is computed ("InitConfReplicas")</li> <li>Output, state and topology of replica simulations ("MdrunOutputs")</li> </ul> A self-contained Python script (compute-visco.py) for the computation of viscosity from the output of an ensemble of simulations is provided. Integrals used to quantify viscosity via Einstein's relation can be obtained from energy output files (.edr) by running: <pre><code>gmx energy -f ener.edr -evisco -eviscoi -vis</code></pre> Simulations are performed with Gromacs. We refer to the code documentation for further information (<a href="https://manual.gromacs.org/">https://manual.gromacs.org/</a>). References: [1] B. Hess, Determining the shear viscosity of model liquids from molecular dynamics simulations, J. Chem. Phys. 116, 209–217 (2002) <a href="https://doi.org/10.1063/1.1421362">https://doi.org/10.1063/1.1421362</a> [2] Y. Zhang et al., Reliable Viscosity Calculation from Equilibrium Molecular Dynamics Simulations: A Time Decomposition Method, J. Chem. Theory Comput. 2015, 11, 3537−3546, <a href="https://doi.org/10.1021/acs.jctc.5b00351">https://doi.org/10.1021/acs.jctc.5b00351</a>

Equilibrium contact angle of acqueous glycerol on a silica-like surface from Molecular Dynamics

This dataset contains the results of Molecular Dynamics simulations of quasi-2D water-glycerol liquid droplets, spreading on silica-like surfaces. The goal of the simulations is to quantify the equilibrium contact angle of said droplets. The pattern "Glycerol***" refers to the mass fraction of glycerol ("000": pure water, "100": pure glycerol). Each folder contains configuration files and compressed output molecular trajectories. The contact angle is computed from density maps binned on-the-fly using a customized Gromacs version (<a href="https://github.com/pjohansson/gromacs-flow-field">https://github.com/pjohansson/gromacs-flow-field</a>); frames are placed in a tarball ("flow-***p.tar.gz"). The zipped folder 'scripts.zip' contains a self-contained library of functions to read density maps and a Jupyter notebook with an example of density reading and plotting. Simulations are performed with Gromacs. We refer to the code documentation for further information (<a href="https://manual.gromacs.org/">https://manual.gromacs.org/</a>).

opencc-by-4.0May 2023View details →

Imaging data from "Live-cell 3D single-molecule tracking reveals modulation of enhancer dynamics by NuRD"

3D 20ms, 3D 500ms and 2D dCas9 raw videos, localisation, tracking and trajectory analysis data From 'Live-cell 3D single-molecule tracking reveals modulation of enhancer dynamics by NuRD" (2021). Biorxiv. https://doi.org/10.1101/2020.04.03.003178

Research data supporting: "Detecting dynamic domains and local fluctuations in complex molecular systems via timelapse neighbors shuffling"

This repository contains the set of data shown in the paper "Detecting dynamic domains and local fluctuations in complex molecular systems via timelapse neighbors shuffling" published on PNAS (DOI: 10.1073/pnas.2300565120).

Biochemical networks with simulation-based estimations of dynamical properties

This datasets collection was first introduced in the article:  <a href="https://academic.oup.com/bioinformatics/article/39/11/btad678/7407341" target="_blank" rel="noopener">Exploiting the structure of biochemical pathways to investigate dynamical properties with neural networks for graphs</a>. (Bioinformatics 2023)   The collection contains three datasets that contain information about three dynamical properties computed on a set of 483 biochemical pathways downloaded from the BioModels database. The three dynamical properties are: <ul> <li>robustness</li> <li>sensitivity</li> <li>monotonicity</li> </ul> The files are organized as follows: <ol> <li>The `pathways` directory contains 483 files in .dot format for each biochemical pathway downloaded from the BioModels database (May 2021), represented in Petri net format (see <a href="https://doi.org/10.5220/0008964700320043">this article</a> for the exact definition). The file name is the ID of the pathway in the BioModels database.</li> <li>The other folders contain one .csv file for each property. A single .csv file contains 4 columns: <ol> <li>`PathwayID`: the ID of the Pathway in the BioModels database</li> <li>`Input`: the input molecular species on which the property has been assessed</li> <li>`Output`: the output molecular species on which the property has been assessed</li> <li>`Property`: the value of the property assessed with numerical simulations on the pathway for that particular input/output species pair.</li> </ol> </li> <li>The `loader.py` file is an optional script that allows to use the data in python. The script requires that the libraries `networkx`, `pandas`, and `pydot` are installed in the target machine.</li> </ol>

Data and code for "Turning tables: food availability shapes dynamic aggressive behaviour among asynchronously hatching siblings in red kites Milvus milvus"

Abstract Aggression represents the backbone of dominance acquisition in several animal societies, where the decision to interact is dictated by its relative cost. Among siblings, such costs are weighted in the light of inclusive fitness, but how this translates to aggression patterns in response to changing external and internal conditions remains unclear. Using a null-model-based approach, we investigate how day-to-day changes in food provisioning affect aggression networks and food allocation in growing red kite (Milvus milvus) nestlings, whose dominance rank is largely dictated by age. We show that older siblings, irrespective of age, change from targeting only close-aged peers (close-competitor pattern) when food provisioning is low, to uniformly attacking all other peers (downward heuristic pattern) as food conditions improve. While food allocation was generally skewed towards the older siblings, the youngest sibling in the nest increased its probability of accessing food as more was provisioned and as downward heuristic patterns became more prominent, suggesting that different aggression patterns allow for catch-up growth after periods of low food. Our results indicate that dynamic aggression patterns within the nest modulate environmental effects on juvenile development by influencing the process of dominance acquisition and potentially impacting the fledging body condition, with far-reaching fitness consequences.

Interaction of biomolecules with anatase, rutile and amorphous TiO2 surfaces: A molecular dynamics study / supplement

<ul> <li>S1 File - Short videos representing the interaction of the 6 different biomolecules (KGD, KRSR, LGD, LRSR, RGD and RSR) with the 3 different TiO2 surface (anatase, amorphous and rutile).</li> <li>S2 File - A representative trajectory file of the LRSR peptide and amorphous TiO2 surface MD simulation without the ions and water molecules.</li> <li>S3 File - Force-distance curve data for the binding energy calculations.</li> </ul>

opencc-by-4.0Dec 2021View details →

Dynamic Binaural Processing (sBTRF) data

This dataset is associated with a publication exploring processing of dynamic binaural cues.

Data from: Biochemical, structural and dynamical characterizations of the lactate dehydrogenase from Selenomonas ruminantium provide information about an intermediate evolutionary step prior to complete allosteric regulation acquisition in the super family of lactate and malate dehydrogenases.

This data accompanies the paper entitled Biochemical, structural and dynamical characterizations of the lactate dehydrogenase from Selenomonas ruminantium provide information about an intermediate evolutionary step prior to complete allosteric regulation acquisition in the super family of lactate and malate dehydrogenases. The zip archive contains the results of molecular dynamics simulations of the 2 systems investigated in the paper: S. rum and T. mar LDHs. The systems have been simulated at 315 K for S. rum and 340 K for T. mar. Final configurations of the proteins after productions are provided for all the systems in GRO Gromos87 format. Trajectories with the positions of the proteins every 100 ps are provided for all the systems in XTC gromacs format.