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1,548 results for “Trajectories”
Trajectory data and TraJClassifier settings
<p>The zip file contains a folder for each applied method. Each folder contain two files:</p> <p>settings.xls: These are the settings used for the TraJClassifier</p> <p>tracks.xml: This file contains the trajectory data measured by TrackMate. It can be loaded into the TraJClassifier plugin.</p>
Centered trajectories of NMRlipids II
<p>Collection of molecular dynamics simulation trajectories previously published in the NMRlipids community of Zenodo, and the related input files needed for their analysis. These centered (origin at the lipid bilayer center) trajectories were used in the NMRlipids II project. In addition to trajectories, files containing lipidwise C-H order parameters (for the beta and alpha segments of the PC-lipid headgroup) for each frame are provided.</p> <p>Note that this upload is provided just for the ease of repetition of the analysis by the interested reader of the NMRlipids II publication <em>Molecular electrometer and binding of cations to phospholipid bilayers</em> (http://dx.doi.org/10.1039/c6cp04883h). <strong>If you use any data provided in here for your own work, please cite the corresponding original uploads!</strong></p>
Simulations with different antennas reconstructing the same trajectory
<p>The ZIP-file "OneTrajectoryManyAntennasExperiments.zip" contains archive of simulations of an array of different antennas reconstructing the same trajectory. </p> <p>The files with names<br> <antenna number>antenna_TDOAs<bat>.cvs<br> contain baseline TDOAs, our method TDOAs and real TDOAs for each time moment </p> <p>The files with names<br> <antenna number>antennaTraj<bat>_xyzBaseline.csv<br> contain trajectory reconstructed using baseline TDOAs: x,y,z values for each time moment </p> <p>The files with names<br> <antenna number>antennaTraj<bat>_OurMethod.csv<br> contain trajectory reconstructed using TDOAs calculated by our method: x,y,z values for each time moment </p> <p>The files with names<br> ALLantennasTraj<bat>_xyzBaselineAndOur<br> ALLantennas_TDOAs<bat><br> contain Matlab figures and pictures of all trajectories and TDOAs.</p> <p>Archive "signalsAndCorrelations.zip" contains signals captured by microphones and correlations between them.<br> </p>
Molecular dynamics trajectory videos for high-affinity short peptides targeting BamA protein of Candidatus liberibacter asiaticus
<p>Molecular dynamics trajectory videos and trajectory analysis reports for high-affinity short peptides targeting BamA protein of <em>Candidatus</em> liberibacter asiaticus</p>
DNMT3A/B MD Trajectories
<p>Ensembles extracted from the MD trajectories of DNMT3A-CGC/T/A/G and DNMT3B-CGG/A/T/C complexes. For each complex, we generated a 500 ns long trajectory and recorded structural snapshots at each 0.5 ns, leading to 1001 conformers per complex.</p> <p>All the MD related parameter files and trajectory analysis scripts are deposited at <a href="https://github.com/CSB-KaracaLab/DNMT3AB_specificity/">https://github.com/CSB-KaracaLab/DNMT3AB_specificity/</a></p> <p>Our work is described in detail at <a href="https://www.biorxiv.org/content/10.1101/2024.02.07.579311v3">https://www.biorxiv.org/content/10.1101/2024.02.07.579311v3</a></p> <p> </p>
Characterizing Spatially Continuous Variations in Tissue Microenvironment through Niche Trajectory Analysis - Dataset
<p><span>Recent technological developments have made it possible to map the spatial organization of a tissue at the single-cell resolution. However, computational methods for analyzing spatially continuous variations in tissue microenvironment are still lacking. Here we present ONTraC as a strategy that constructs niche trajectories using a graph neural network-based modeling framework. Our benchmark analysis shows that ONTraC performs more favorably than existing methods for reconstructing spatial trajectories. Applications of ONTraC to public spatial transcriptomics datasets successfully recapitulated the underlying anatomical structure, and further enabled detection of tissue microenvironment-dependent changes in gene regulatory networks and cell-cell interaction activities during embryonic development. Taken together, ONTraC provides a useful and generally applicable tool for the systematic characterization of the structural and functional organization of tissue microenvironments.</span></p>
Molecular dynamics trajectory for CsPbI3
<p>This record provides a molecular dynamics trajectories for CsPbI3 generated via GPUMD using the input files included in this record. This trajectories are used in one of the examples that demonstrate the functionality of the <a href="https://dynasor.materialsmodeling.org">dynasor package</a>.</p>
Molecular dynamics trajectories related to manuscript: SARS-CoV-2 nsp3 and nsp4 are minimal constituents of a pore spanning replication organelle
<p>This dataset contains two folders, each with sequentially numbers coordinates files for all-atom molecular dynamics trajectories related to the manuscript "SARS-CoV-2 nsp3 and nsp4 are minimal constituents of a pore spanning replication organelle" by Zimmermann et al. Each folder contains PDB and PSF files specifying the components of each system depicted in Fig. S10 of that manuscript as well as 200 sequentially named DCD files, each containing 5 nanoseconds of a 1 microsecond trajectory.</p>
UED and trajectory dataset – photochemistry of thiophenone
<p># UED_thiophenone</p><p>---</p><p>Dataset for the 15uJ MeV-UED experiment on thiophenone (20201103_2242_run32_15uJ) and Trajectories of thiophenone used to analyze the UED results (trajectories_xyz).</p><p> </p><p>## Description of the data and file structure</p><p> </p><p>Directory '20201103_2242_run32_15uJ.zip' contains the raw data of the UED experiment conducted on thiophenone and analyzed in the main text of the article. The label of each file corresponds to the delay of the pump/probe setup. The format of each image is tif.</p><p> </p><p>Directory 'trajectories_xyz.zip' contains xyz trajectories of nonadiabatic molecular dynamics (TSHx.xyz) and subsequent ab initio molecular dynamics (AIMDx.xyz). The 'x' label the trajectory (43 trajectories, TSH+AIMD, in total).</p><p> </p><p> </p><p>## Sharing/Access information</p><p> </p><p>NA</p><p> </p><p>## Code/Software</p><p> </p><p>NA</p><p> </p>
3D trajectories for plants' tendril
Open the record for dataset details and reuse information.
Data and R-Scripts for the manuscript "Arctic tundra ecosystems under fire – potential trajectories for stable state shifts"
Open the record for dataset details and reuse information.
DELVE: Feature selection for preserving biological trajectories in single-cell data
<p>Contains preprocessed single-cell data and metadata for feature selection. Preprocessed adata objects can be accessed using the <em>read_h5ad</em> function in anndata. Also contains the source data files for reproducing the Figures and Supplementary Figures referenced in the manuscript.</p> <ul> <li>The RPE iterative indirect immunofluorescence imaging dataset (adata_RPE.h5ad) from Ref. (<a href="https://doi.org/10.1016/j.cels.2021.10.007">https://doi.org/10.1016/j.cels.2021.10.007</a>) was originally downloaded from the Zenodo repository (<a href="https://doi.org/10.5281/zenodo.4525425">https://doi.org/10.5281/zenodo.4525425</a>).</li> <li>The PDAC iterative indirect immunofluorescence imaging datasets (listed below) were originally downloaded from the Zenodo repository (<a href="https://doi.org/10.5281/zenodo.7860332">https://doi.org/10.5281/zenodo.7860332</a>). <ul> <li>adata_PDAC_BxPC3_control.h5ad</li> <li>adata_PDAC_CFPAC_control.h5ad</li> <li>adata_PDAC_HPAC_control.h5ad</li> <li>adata_PDAC_MiaPaCa_control.h5ad</li> <li>adata_PDAC_Pa01C_control.h5ad</li> <li>adata_PDAC_Pa02C_control.h5ad</li> <li>adata_PDAC_Pa16C_control.h5ad</li> <li>adata_PDAC_PANC1_control.h5ad</li> <li>adata_PDAC_UM53_control.h5ad</li> </ul> </li> <li>The CD8+ T cell differentiation dataset (adata_CD8.h5ad) from Ref. (<a href="https://doi.org/10.1016/j.cels.2021.10.007">https://doi.org/</a><a href="https://doi.org/10.1126/sciimmunol.aaz6894">10.1126/sciimmunol.aaz6894</a>) was originally downloaded from the Gene Expression Omnibus under the accession code GSE131847 (<a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE138266">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE131847</a>).</li> <li>The definitive endoderm differentiation dataset (adata_DE.h5ad) contains multiplexed single-cell RNA sequencing data profiling the differentiation of human embryonic stem cells into the definitive endoderm. </li> </ul>
Trajectories of the plants for the two conditions
Open the record for dataset details and reuse information.
Identification of Potential IL4I1 Inhibitors through Structure-Based Virtual Screening and Molecular Dynamics Simulations, Molecular dynamics trajectory file
<p>Dataset for molecular dynamics simulations of the article: Identification of Potential IL4I1 Inhibitors through Structure-Based Virtual Screening and Molecular Dynamics Simulations.</p> <p><a href="../api/records/10473570/draft/files/First_600ns_MD.rar/content" target="_blank" rel="noopener noreferrer">First_600ns_MD.rar</a> contains the 600ns molecular dynamics simulation trajectory file of IL4I1-FAD-CIT complex using desmond.</p> <p><a href="../api/records/10473570/draft/files/Second_500ns_MD_ZL35_F963.rar/content" target="_blank" rel="noopener">Second_500ns_MD_ZL35_F963.rar </a>contains the 500ns molecular dynamics simulation trajectory file of IL4I1-FAD-ZL35 complex, which initial conformation of this part of dynamics simulation was obtained by docking the conformation of the 963rd frame from the first dynamics simulation with ZL35 through induced fit.</p> <p>script.rar include scripts and calculation methods for free energy landscape, RMSD matrix, and thermol MM/GBSA.</p>
Parcels-WAOM model data: Lagrangian particle trajectories
<p>This data set includes the results of Lagrangian particle tracking experiments with Parsels in Weddell and Ross seas. </p> <p>The following information for each particle is stored once a day: longitude (lon in files), latitude (lat), time (time), depth (z), temperature (temp), salinity (sal), ice draft (ice).</p> <p>Each *.zip archive contains one experiment in netcdf file for one of the seas (Weddell or Ross seas) and for one of four seasons during 20 years of simulations. </p>
Supporting MD trajectories for the paper "In Situ Captured Antibacterial Action of Membrane-Incising Peptide Lamellae"
<p>Source data and molecular dynamic trajectories for the article "In Situ Captured Antibacterial Action of Membrane-Incising Peptide Lamellae"</p> <p>New compounds with unique mechanisms of action are needed to combat the growing issue of antimicrobial resistance. Supramolecular assemblies, which combine the complex membrane attacking mechanisms of natural host defense peptides with the improved biostability of non-natural compounds offer a promising alternative to current small molecule antibiotics. However, for such membrane-targeting compounds the direct visual insight on the toxic agents in bacteria is still lacking. To this end, we employed a design strategy focusing on an inducible assembly mechanism and utilized electron microscopy (EM) to follow the formation of supramolecular peptide structures triggered by bacterial cell surface lipopolysaccharides (LPS). Inspired by the alternating chirality backbone pattern of some effective peptide antimicrobials, we designed lysine-rich heterochiral β3-peptides, termed lamellin-2K and lamellin-3K, with optimal residual spacing for enhanced coordination on the phosphate groups of LPS. Combined molecular dynamics simulations (MD), EM and bacterial assays confirmed that the phosphate-induced conformational change of these lamellins led to the formation of thin, striped lamellar layers, where each stripe represents double arrays of H-bonded peptide molecules that are interconnected by phosphate ions. EM micrographs of Gram-negative bacteria show that the lamellae incised the cell envelope, while leakage and antibacterial activity assays prove that growth inhibition starts already at submicromolar concentrations. Detailed image analysis demonstrated that the lamellae penetrating deep into the bacterial cell have a rather uniform size distribution and, surprisingly, only a few of these supramolecules are sufficient to cause major cell wall damage making them efficient in destroying target cells. Our findings also provide a missing mechanistic link for membrane-targeting agents, connecting how the antibiotic mechanism is built up from individual molecules through on-site formation of the active supramolecules that lead to bactericidal activity.</p> <p>Molecular dynamics trajectories from the production runs of single beta-peptide strands in water + 150 mM NaCl + 50:1 MePO4^(2-):peptide. Altogether 8 runs were performed, each one starting from a different helical conformation (H10, H12 and H14, both positive and negative winding) of the peptide. In the first half (500 ns) of the simulation, the intra-chain hydrogen bonds responsible for the actual helix were kept together by distance restraints. In the second half (again 500 ns), these restraints were instantaneously lifted and the system was left to evolve from the same state. In all cases the helical structure unwound in a very short time (under 100 ns), and did not refold in any helix.</p>
Disease trajectories in hospitalized COVID-19 patients are predicted by clinical and peripheral blood signatures representing distinct lung pathologies
<p><span>COVID-19 is characterized by a broad range of symptoms and disease trajectories. Understanding the correlation between clinical biomarkers and lung pathology over the course of acute COVID-19 is necessary to understand its diverse pathogenesis and inform more precise and effective treatments. Here, we present an integrated analysis of longitudinal clinical parameters, peripheral blood biomarkers, and lung pathology in COVID-19 patients from the Brazilian Amazon. We identified core clinical and peripheral blood signatures differentiating disease progression between recovered patients from severe disease and fatal cases. Signatures were heterogenous among fatal cases yet clustered into two patient groups: “early death” (< 15 days of disease until death) and “late death” (> 15 days). Progression to early death was characterized systemically and in lung histopathology by rapid, intense endothelial and myeloid activation/chemoattraction and presence of thrombi, associated with SARS-CoV-2<sup>+</sup> macrophages. In contrast, progression to late death was associated with fibrosis, apoptosis and abundant SARS-CoV-2<sup>+</sup> epithelial cells in post-mortem lung, with cytotoxicity, interferon and Th17 signatures only detectable in the peripheral blood 2 weeks into hospitalization. Progression to recovery was associated with higher lymphocyte counts, Th2 and anti-inflammatory-mediated responses. By integrating ante-mortem longitudinal systemic and spatial single-cell lung signatures, we defined an enhanced set of prognostic clinical parameters predicting disease outcome for guiding more precise and optimal treatments.</span><span> Finally, this study represents a major advance in the investigation of acute respiratory infections by integrating serial clinical data and peripheral blood samples with histopathological and </span><span>spatially-resolved single-cell </span><span>analyses of post-mortem lung samples.</span></p>
UAS Trajectory Model Dynamics at different flight heights: An In-depth Analysis of PPK Georeferencing Results for an Urban Area
<p>In-depth analysis of the PPK georeferencing results when using three different Continuously Operating Reference Station (CORS) stations and one local base station.</p>
GPS trajectories of tourists in Öregrund 2022 from INCULTUM Sweden Pilot
<p>This dataset is part of ongoing work about changes in tourists' behaviour in Öregrund.</p>
Dataset for "Predicting the growth trajectory and yield of greenhouse strawberries based on knowledge-guided computer vision"
<h2>Overall</h2> <p>A strawberry dataset for the paper "Qi Yang, Licheng Liu, Junxiong Zhou, Mary Rogers, Zhenong Jin, 2024. Predicting the growth trajectory and yield of greenhouse strawberries based on knowledge-guided computer vision, Computers and Electronics in Agriculture, 220, 108911. <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.compag.2024.108911" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.compag.2024.108911</a>"</p> <h2>Plant traits measurements</h2> <p>The folder "measurement.zip" includes treatment-level and fruit-level ground truth data. </p> <h3>Treatment-level</h3> <pre><code>data_dryMatter_2022.csv data_dryMatter_2023.csv data_freshMatter_2022.csv data_freshMatter_2023.csv data_fruitNumber_2022.csv data_fruitNumber_2023.csv data_plantBiomass_2022.csv data_plantBiomass_2023.csv</code></pre> <h3>Fruit-level</h3> <p>Fruit conditions with five classes, 1-5 represent Normal, Wizened, Malformed, Wizened & Malformed, and Overripe, respectively.</p> <pre><code>data_size_freshWeight_condition_2022_0N.csv data_size_freshWeight_condition_2022_50N.csv data_size_freshWeight_condition_2022_100N.csv data_size_freshWeight_condition_2022_150N.csv</code></pre> <p>Fruit size for tagged fruits</p> <pre><code>data_taggedFruit_diameter_2022.csv data_taggedFruit_diameter_2023.csv data_taggedFruit_length_2022.csv data_taggedFruit_length_2023.csv</code></pre> <p>Fresh yield and lifespan for tagged fruits (only available in experiment 2023)</p> <pre><code>data_taggedFruit_freshMatter_2023.csv data_taggedFruit_lifespan_2023.csv</code></pre> <h3>Weather data</h3> <pre><code>weather_daily_2022.csv weather_daily_2023.csv</code></pre> <h2>Image data with label</h2> <h3>Object and phenology detection</h3> <p>The folder "strawberry_img_random.zip" contains images and the corresponding JSON labels for object and phenological stages detection.</p> <h3>Fruit size and decimal phenological stage</h3> <p>The folder "strawberry_img_tagged.zip" contains images and the corresponding JSON labels for fruit size and decimal phenological stages detection.</p> <pre><code>For example, "label": "small g, 8.84, 7.62, 0.4", This label means the fruit has an 8.84mm diameter and 7.62mm length, with the main stage being small green and the decimal stage being DS-4 </code></pre> <h3>Merge and split Data</h3> <p>A Python script, "datasetProcessing.py", can be used to merge and split the image data into training and testing set.</p> <h3>Pre-trained models</h3> <p>models.zip</p> <p> </p> <p><em>Data collector: Dr. Qi Yang, University of Minnesota, USA. Email: qiyang577@gmail.com</em></p> <p><em>All the files belong to Prof. Zhenong Jin, University of Minnesota, USA. Email: jinzn@umn.edu</em></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)
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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.