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11,506 results for “Dynamics”
Cascade Project at North Temperate Lakes LTER High Frequency Sonde Data from Spatial Dynamics Experiment 2018 - 2019
High-frequency continuous data for temperature, dissolved oxygen, pH, chlorophyll-a, and phycocyanin in Paul Peter lakes from mid-May to early September for the years 2018 and 2019. Inorganic nitrogen and phosphorus were added to Peter in 2019, while Paul Lake was an unfertilized reference.
SBC LTER: Reef: Kelp Forest Community Dynamics: Kelp Forest Data to support "Estimating biomass of benthic kelp forest invertebrates from body size and percent cover"
These data describe quantitative relationships between wet mass and length or wet mass and percent cover, and conversion factors to transform wet mass into dry mass, shell-free and decalcified dry mass, and ash-free dry mass for 84 species of benthic macroinvertebrates common to giant kelp forests in southern California. Data are based on organisms collected from sites in the Santa Barbara Channel between April 2010 and May 2014. These measurements are intended to facilitate the conversion of invertebrate abundance into common metrics of biomass, for quantitative studies of community dynamics, trophic interactions, energy flow and biodiversity. Converting numerical abundance (i.e., organism density) to biomass requires information on the relationship between individual size and biomass. For colonial and small aggregating taxa that are numerous and indistinct, measures of abundance are usually proportional (e.g., percent cover). Hence, converstions are taxa-specific, based on either size or cover, and a variety of metrics of species biomass are included, e.g., wet mass, shell-free wet mass, ash-free dry mass. Data are published in Reed, D. C, J. C. Nelson, S. L. Harrer, and R. J. Miller, Estimating biomass of benthic kelp forest invertebrates from body size and percent cover data. Marine Biology. DOI: 10.1007/s00227-016-2879-x. From the paper abstract: The inability to compare different measures of species abundance (such as density and percent cover) or different metrics of species biomass (such as wet mass and ash-free dry mass) hampers quantitative studies of community dynamics, trophic interactions, energy flow and biodiversity. This has been especially problematic for the dynamic and highly productive communities inhabiting shallow reefs in temperate seas where varied metrics are commonly used to characterize the abundance and biomass of different suites of species. Regressions for all 84 species were highly significant and regression fits were very good for mos
Gunnison's Prairie Dog Restoration Experiment (GPDREx): Population Dynamics within Grasslands at the Sevilleta National Widlife Refuge, New Mexico
Prairie dogs (Cynomys spp.) are burrowing rodents considered to be ecosystem engineers and keystone species of the central grasslands of North America. Yet, prairie dog populations have declined by an estimated 98% throughout their historic range. This dramatic decline has resulted in the widespread loss of their important ecological role throughout this grassland system. The 92,060 ha Sevilleta NWR in central New Mexico includes more than 54,000 ha of native grassland. Gunnison’s prairie dogs (C. gunnisoni) were reported to occupy ~15,000 ha of what is now the SNWR during the 1960’s, prior to their systematic eradication. In 2010, we collaborated with local agencies and conservation organizations to restore the functional role of prairie dogs to the grassland system. Gunnison’s prairie dogs were reintroduced to a site that was occupied by prairie dogs 40 years ago. This work is part of a larger, long-term study where we are studying the ecological effects of prairie dogs as they re-colonize the grassland ecosystem.
Flow dynamics and pump kinematics in polychaete burrows constructed in a transparent mud analog
We used Particle Tracking Velocimetry (PTV) to measure fluid flow within burrows constructed by the polychaete Alitta succinea in a transparent mud analog. We also measured the kinematics of the undulatory pumping by the polychaete that drives flow through the burrow. The flow velocity data is presented in the spreadsheet worm_burrow_particle_tracking_data.csv and consists of the x and y coordinates (in mm) of each tracked particle, the time at which it was tracked (in seconds) and the velocity of the particle at that time (in mm per second). The ClipID is the reference of the video clip the data is from, and is a unique identifier. The SequenceID is retained between the pump dynamics data and the particle tracking data, because worm kinematics and flow dynamics were recorded simultaneously. Each tracked particle in a given sequence has a unique TrackID. The worm kinematics data consists of the track of the peak of the undulatory wave created as an individual polychaete ventilates its burrow and is presented in the spreadsheet worm_burrow_pump_dynamics_data.csv. The variables included are the x and y coordinates of the wave peak (in mm), the time at which the point was taken (in seconds) and the instantaneous velocity of the wave peak at that time (in mm per second). The ClipID is the reference of the video clip the data is from, and is a unique identifier. The SequenceID is retained between the pump dynamics data and the particle tracking data, because worm kinematics and flow dynamics were recorded simultaneously. Each tracked wave in a given sequence has a unique TrackID. The metadata, in the spreadsheet worm_burrow_metadata.csv, gives the polychaete Individual ID (a unique identifier for each specimen used) for each Clip ID and Sequence ID from the data spreadsheets, the location in the burrow at which the video was taken (between the head of the worm and the burrow entrance is "ahead", between the tail of the worm and the burrow exit is "behind", and a video of
Simulations from the SEIB-DGVM dynamic global vegetation model for the Vegetation Carbon Turnover Intercomparison
<p>Outputs from the SEIB-DGVM dynamic global vegetation model. One forced by CRU-NCEP v5 climate data for the period 1901-2014 and one forced by bias-corrected IPSL-CM5A-LR RCP 8.5 climate data for the period 1901-2099. Only potential natural vegetation was simulated, i.e. no human land-use. Both simulations are at 0.5 x 0.5 degree spatial resolution. Carbon turnover fluxes for live vegetation for each individual turnover-causing process in the model were outputted individually. For a full description of the simulations, please refer to the accompanying paper.</p>
ASPLOS20-AE Artifact Dataset for 'Noise-Aware Dynamical System Compilation for Analog Devices with Legno'
<p>The empirical model database and dataset for the ASPLOS 2020 Paper 'Noise-Aware Dynamical System Compilation for Analog Devices with Legno'</p>
Data Accompanying "Dynamics of Water Absorption in Callovo-Oxfordian Claystone Revealed With Multimodal X-Ray and Neutron Tomography"
<p>These are the datasets analysed in the publication "Dynamics of Water Absorption in<br> Callovo-Oxfordian Claystone Revealed With Multimodal X-Ray and Neutron Tomography" by Stavropoulou <em>et al.</em> in 2020 in Frontiers in Earth Science, DOI: <a href="https://doi.org/10.3389/feart.2020.00006">https://doi.org/10.3389/feart.2020.00006</a></p> <ol> <li>File 1 contains the 3D reconstructed x-ray and neutron tomography volumes analysed in the paper. State 002 is taken as a reference and the greylevels of all images in the times series for both x-ray and neutrons are rescaled using two characteristic image features (top-cap and air in the case of x-rays) linearly to align with 002. Neutron volumes are rescaled to the same pixel size as 2-bin x-ray volumes, and a mean registration is applied to align neutrons with x-rays.<br> Furthermore, a bilateral filter is applied to the neutron tomographies (domain sigma = 1, range sigma=3000).<br> Full scale images are available at <a href="https://doi.ill.fr/10.5291/ILL-DATA.UGA-42">https://doi.ill.fr/10.5291/ILL-DATA.UGA-42</a><br> </li> <li>File 2 contains the joint histograms for registered pairs of images, as visible in Figure 4 and Figure 5.<br> </li> <li>File 3 contains the results of the digital volume correlation performed with the <a href="https://ttk.gricad-pages.univ-grenoble-alpes.fr/spam/intro.html">spam</a> tookit.<br> The overall "registration" is used to create Figure 6<br> The global correlations available in "gdic" are used to create Figures 7, 8 and 9.</li> </ol>
A Computational Theory for the Emergence of Grammatical Categories in Cortical Dynamics
<p>The file <strong>Corpora.txt </strong>keeps the corpus used to train the model and the different instances of the classifier. It is basically a text file with one sentence per line from the original corpus called <strong>test.tsv</strong> available at <a href="https://github.com/google-research-datasets/wiki-split.git">https://github.com/google-research-datasets/wiki-split.git</a>. We eliminated punctuation marks and special characters from the original file putting each sentence per line.</p> <p><strong>Enju_Output.txt </strong>holds the outputs generated by Enju in -so mode (Output in stand-off format) using Corpora.txt as input. This file has basically a natural language English per-sentence parse with a wide-coverage probabilistic for HPSG grammar.</p> <p>The file <strong>Supervision.txt </strong>keeps the grammatical tags of the corpus. This file holds a tag per word and each tag is situated in a single line. Sentences are separated by one empty line while tags from words in the same sentence are located in adjacent lines.</p> <p>The file<strong> Word_Category.txt</strong> carries the coarse-grained word category information needed by the model and introduced in it by apical dendrites. Each word in the corpus has a word-category tag which provides additional constraints to those provided by lateral dendrites. This file contains a tag per word and each tag is situated in a single line. Sentences are separated by one empty line while tags from words in the same sentence are located in adjacent lines.</p> <p>The file <strong>SynSemTests.xlsx</strong> keeps all the grammar classification results as well as the statistical analysis in the classification tests.</p>
The MedAfriCarbon radiocarbon database and web application. Archaeological dynamics in Mediterranean Africa, ca. 9600-700 BC
<p>MedAfriCarbon radiocarbon database and web app are outcomes of the <em>MedAfrica Project —Archaeological deep history and dynamics of Mediterranean Africa, ca. 9600-700 BC</em>. The dataset presented here includes a collection of <strong>1584</strong> calibrated archaeological 14C dates from <strong>1587</strong> samples collected from <strong>368</strong> sites located in Mediterranean Africa (plus some additional dates whose published information is incomplete). The majority of the dates are linked to cultural and environmental variables, notably the presence/absence of different domestic/wild species and specific material culture.</p> <ul> <li><strong>1.0.3</strong> _27 Feb 2020_– Official public JOAD release (includes JOAD DOI and volume numbers). Includes a few minor error corrections.</li> <li><strong>1.0</strong> _30 Jan 2020_— First public release of the dataset on Zenodo.</li> </ul>
R code and radiocarbon dates to reproduce figures and results of our paper "Population dynamics ..."
<p>R Codes and dataset to reproduce figures and results of the paper <strong><em>Population dynamics during the Neolithic transition and the onset of megalithism in Portugal according to summed probability distribution of radiocarbon determinations</em>. </strong></p>
Molecular dynamics trajectories for "Structure and chemistry of graphene oxide in liquid water from first principles"
<p>This dataset contains molecular dynamics (MD) trajectories from the paper <a href="https://doi.org/10.1038/s41467-020-15381-y">“Structure and chemistry of graphene oxide in liquid water from first principles”, F. Mouhat, F.-X. Coudert and M.-L. Bocquet, <em>Nature Commun.</em>, <strong>2020</strong>, <em>11</em>, 1566, 10.1038/s41467-020-15381-y</a></p> <p> </p>
All Atom Molecular Dynamics Simulations of Lopinavir at the Binding Pocket of SARS-CoV2 Main Protease
<p>Data includes all of the trajectories (2000) of classical all-atom molecular dynamics (MD) simulations of lopinavir at the binding pocket of SARS-CoV2 main protease target. In order to decrease the size of the file only protein and ligand trajectories were provided. Simulation has been performed with Desmond. Protein–ligand complexes were obtained by Glide/SP docking program. Complex was placed in the cubic boxes with explicit TIP3P water models that have 10.0 Å thickness from surfaces of protein. The system is neutralized by adding counter ions, and salt solution of 0.15M NaCl was also used to adjust the concentration of the systems. The long-range electrostatic interactions were calculated by the particle mesh Ewald method. A cutoff<br> radius of 9.0 Å was used for both van der Waals and Coulombic interactions. The temperature was set as 310K initially, and Nose–Hoover thermostat was used for adjustment. Martyna–Tobias–Klein protocol was employed to control the pressure, which was set at 1.01325 bar. The time-step was assigned as 2.0 fs. The default values were used for minimization and equilibration steps, and finally 500 ns production run was performed for the simulations.</p>
Molecular dynamics simulation data of designed cyclic peptide (ligand-only)
<p>Trajectories of <strong>ligand-only </strong>simulation and simulation set-up files of designed cyclic peptide as MDM2 binders. <br> The original paper of these designed cyclic peptide: Danelius, E., Pettersson, M., Bred, M., Min, J., Waddell, M. B., Guy, R. K., et al. (2016). Flexibility is important for inhibition of the MDM2/p53 protein–protein interaction by cyclic β-hairpins. <em>Org. Biomol. Chem.</em>, <em>14</em>(44), 10386–10393. http://doi.org/10.1039/C6OB01510G</p>
Molecular dynamics simulation data of regulatory ACT domain dimer of human phenylalanine hydroxylase (PAH)
<p>Raw data of molecular dynamics simulations of regulatory ACT domain dimer.</p> <p><strong>binding.zip</strong>: simulation starting from 21 dimer conformations with 19 Phe ligand </p> <p><strong>bound.zip</strong>: simulation starting from dimer with bound Phe ligand</p> <p><strong>dimer.zip</strong>: simulation starting from 21 dimer conformations simulation</p> <p>Simulation setup files are also included in each folder.</p> <p>Details can be found in this paper:</p> <p><strong>Yunhui Ge</strong>, Elias Borne, Shannon Stewart, Michael R. Hansen, Emilia C. Arturo, Eileen K. Jaffe and Vincent A. Voelz. <a href="http://www.jbc.org/content/293/51/19532"><em>Simulation of the regulatory ACT domain of human PAH unveil the mechanism of phenylalanine binding.</em></a> J. Biol. Chem., 2018, 293(51), pp 19532-19543</p>
Molecular dynamics simulation data of regulatory ACT domain monomer of human phenylalanine hydroxylase (PAH)
<p>Raw data of molecular dynamics simulations of regulatory ACT domain monomer.</p> <p><strong>binding.zip</strong>: simulation starting from 21 monomer conformations with 19 Phe ligand </p> <p><strong>bound.zip</strong>: simulation starting from monomer with bound Phe ligand</p> <p><strong>monomer_only.zip</strong>: simulation starting from 21 monomer conformations simulation</p> <p>Simulation setup files are also included in each folder. Adaptive sampling data are also included in <strong>monomer </strong>and <strong>binding</strong> simulations.</p> <p>Details can be found in this paper:</p> <p><strong>Yunhui Ge</strong>, Elias Borne, Shannon Stewart, Michael R. Hansen, Emilia C. Arturo, Eileen K. Jaffe and Vincent A. Voelz. <a href="http://www.jbc.org/content/293/51/19532"><em>Simulation of the regulatory ACT domain of human PAH unveil the mechanism of phenylalanine binding.</em></a> J. Biol. Chem., 2018, 293(51), pp 19532-19543</p>
An information theory-based machine learning approach to detecting functionally conserved and coordinated protein dynamics
<p>The application of machine learning classification to the molecular dynamics of the functional states of protein allows for application of an information theoretic framework familiar to traditional bioinformatics. The functional states of proteins involving binding interactions with partners comprised of protein, DNA or small molecules can first be defined in a binary fashion (i.e. bound vs unbound), subsequently simulated in molecular dynamics software, and then employed as a comparative training set for a binary machine learning classifier capable of discerning the complex dynamical consequences of binding interaction. This learner can subsequently be deployed on new simulations of the functionally bound state to validate its ability to recognize the molecular motions that are supporting binding function. Regions of proteins with functionally conserved dynamics will induce significant local correlations in learning performance across independent validation runs. Through case studies of Rbp subunit 4/7 interaction in RNA Pol II and DNA-protein interactions of TATA binding protein, we demonstrate this method of detecting functionally conserved protein dynamics. We also demonstrate how Shannon information, relative entropy and mutual information can be applied to these binary classification states of dynamic simulations in order to compare dynamics and identify concerted motions involved in dynamic interactions across sites.</p>
Molecular dynamics simulation data of designed β-hairpins
<p>Raw simulations data (protein only) and simulation set-up files of designed β-hairpins. More details can be found in this paper: </p> <p>Yunhui Ge, Brandon Kier, Niels H. Andersen and Vincent A. Voelz. <a href="https://pubs.acs.org/doi/10.1021/acs.jcim.7b00132"><em>Computational and experimental evaluation of designed beta-cap hairpins using molecular simulations and kinetic network models.</em></a> J. Chem. Inf. Model., 2017, 57 (7), pp 1609–1620</p>
Replica exchange molecular dynamics simulation data of designed β-hairpins (implicit solvent, AMBER ff96)
<p>Raw REMD simulation data (protein only) of designed β-hairpins. AMBER ff96 and implicit solvent model is used. More details can be found in this paper: </p> <p>Yunhui Ge, Brandon Kier, Niels H. Andersen and Vincent A. Voelz. <a href="https://pubs.acs.org/doi/10.1021/acs.jcim.7b00132"><em>Computational and experimental evaluation of designed beta-cap hairpins using molecular simulations and kinetic network models.</em></a> J. Chem. Inf. Model., 2017, 57 (7), pp 1609–1620</p>
Replica exchange molecular dynamics simulation data of designed β-hairpins (implicit solvent, AMBER ff99SB-ildn)
<p>Raw REMD simulation data (protein only) of designed β-hairpins. AMBER ff99SB-ildn and implicit solvent model is used. More details can be found in this paper: </p> <p>Yunhui Ge, Brandon Kier, Niels H. Andersen and Vincent A. Voelz. <a href="https://pubs.acs.org/doi/10.1021/acs.jcim.7b00132"><em>Computational and experimental evaluation of designed beta-cap hairpins using molecular simulations and kinetic network models.</em></a> J. Chem. Inf. Model., 2017, 57 (7), pp 1609–1620</p>
Plasmonic Nanosensors for the Label-Free Imaging of Dynamic Protein Patterns
<p>Additional data to support our work on "Plasmonic Nanosensors for the Label-Free Imaging of Dynamic Protein Patterns" published in the Journal of Physical Chemistry Letters (DOI: 10.1021/acs.jpclett.0c01400)</p> <p>Movies:<br> - S1: MinVideo_EColi.mp4<br> - S2: MinVideo_DOPC_DOPG_CL.mp4<br> - S3: MinVideo_DOPC_DOPG.mp4<br> Audio Files:<br> - S1: MinSound_EColi.mp4<br> - S2: MinSound_DOPC_DOPG_CL.mp4<br> - S3: MinSound_DOPC_DOPG.mp4</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
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.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.