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10,119 results for “IT Support”
Molecular Simulation of Stapled Peptides: Supporting Material
<p>A compressed (tar-gzip) archive containing input and analysis scripts, along with partial analysis data, for Chapter 14 of Computational Peptide Science: Methods and Protocols (Thomas Simonson, ed.) entitled "Molecular Simulation of Stapled Peptides" by Victor Ovchinnikov, Aravinda Munasinghe, and Martin Karplus; Methods in Molecular Biology, vol. 2405, https://doi.org/10.1007/978-1-0716-1855-4_14, 2022, Springer.</p>
Data supporting: "Bayesian diagnosis of climate feedback evolution and forced temperature response"
<p><strong>This data set supports the paper:<br> Calafat, F. M., & Cael, B. B. (2023). Bayesian diagnosis of climate feedback evolution and forced temperature response, Geophysical Research Letters, submitted.</strong></p> <p>Please cite this paper when using this data set.</p> <p><em>Data description:</em></p> <ul> <li><strong>EBM_estimates.nc:</strong> this file contains Bayesian estimates from the energy balance model, including estimates of the climate feedback parameter and forced global average temperature change.</li> <li><strong>EBM_input_data.nc:</strong> this file contains all of the data used as input to the Bayesian energy balance model.</li> </ul>
Practical Cell Design for PTMA-Based Organic Batteries: an Experimental and Modeling Study - Supporting Dataset
<p>The cycling and impedance data used in the work "Practical Cell Design for PTMA-Based Organic Batteries: an Experimental and Modeling Study" are provided in this repository.<br> The data are reported both as original .txt files with the raw data from the instruments and as processed Matlab files, where the data are structured in cycles.<br> The Excel sheet "Metadata" explains the type of battery associated to each code and file(s).</p> <p><br> </p>
sabasoori23/AGU-Publication-WRR: Supporting Information-Data Set 1
<p>The Effect of the Bridge Piers and Abutment Interaction on Large Wood Accumulation Probability using a Physical Mode</p>
Supporting Data for "Allostery in Protein Tyrosine Phosphatases is Enabled by Divergent Dynamics"
<p>Molecular dynamics topologies (.prmtop), initial coordinates (.inpcrd), and trajectories (.nc) associated with the preprint: https://doi.org/10.1101/2023.07.23.550226. Tarballs are included for each of the six systems, named by the PDB ID for the starting structure and state (ligand/apo). The four replicates of 155ns are included in each tarball in AMBER's netcdf format (.nc). All trajectories have been stripped of solvent and ions and are autoimaged. Input files and an example script for running simulations in AMBER20 are provided (infiles.tar.gz) as well as the topologies and coordinates for the solvated systems (solvated_topologies.tar.gz).</p>
Dataset supporting: Repetitive transcranial magnetic stimulation (rTMS) triggers dose-dependent homeostatic rewiring in recurrent neuronal networks
<p>This dataset supports the Figures in the preprint: 'Repetitive transcranial magnetic stimulation (rTMS) triggers dose-dependent homeostatic rewiring in recurrent neuronal networks' by Anil et. al., <a href="https://www.biorxiv.org/content/10.1101/2023.03.20.533396v1">2023</a>.</p> <p>The code used to genrate this data can be found on the github repository: <a href="https://github.com/swathianil">swathianil </a><a href="https://github.com/swathianil/homeostatic_structural_plasticity_rTMS"> /homeostatic_structural_plasticity_rTMS</a>.</p> <p>To interactively regenerate the figures, follow the Jupyter notebook, GraphPlotter, available in the repository.</p>
Fig. 5. Split support spectrum for the 18S in Reconstruction of Evolutionary History of Pleurostomatid Ciliates (Ciliophora, Litostomatea, Haptoria): Interplay of Morphology and Molecules
Fig. 5. Split support spectrum for the 18S rRNA gene alignment used to construct the phylogenetic network in Fig. 4. Column height represents the number of clade-supporting positions, i.e., putative primary homologies. Column parts above the y-axis represent the in-group partition, while those below the axis correspond to the out-group partition.
Datasets and Supporting Materials for the IPIN 2023 Competition Track 4 (Foot-Mounted IMU based Positioning, offsite-online)
<p>This package contains the datasets and supplementary materials used in the IPIN 2023 Competition.</p> <p><strong>Contents:</strong><br> - IPIN2023_Track4_CallForCompetition_v2.2.pdf: Call for competition including the technical annex describing the competition</p> <p>- 01-Logfiles: This folder contains 2 files for each Trials (Testing, Scoring01, Scoring02)<br> - IPIN2023_T4_xxx.txt : data file containing ACCE, ROTA, MAGN, PRES, TEMP, GSBS, GOBS, POSI frames<br> - IPIN2023_T4_xxx_gnss_ephem.nav : for trajectory estimation.<br> <br> - 02-Supplementary_Materials: This folder contains the datasheet files of the different sensors, a static logfile of about 12 hours that can be used for sensors bias estimation (Allan Variance) and a logfile of about 1 minute that can be used to calibrate the magnetometer sensor (Magnetometer Calibration).</p> <p>- 03-Evaluation: This folder contains the scripts used to calculate the competition metric, the 75th percentile on all evaluation points. It requires Matlab Mapping Toolbox. We also provide ground truth of the 2 scoring trials as 2 MAT and KML files. It contains samples of reported estimations and the corresponding results. Just run script_Eval_IPIN2023.mat</p> <p>We provide additional information on the competition at: https://evaal.aaloa.org/2023/call-for-competition</p> <p> </p> <p><strong>Citation Policy:</strong><br> Please, cite the following works when using the datasets included in this package:</p> <p>Ortiz, M.; Zhu, N.; Ziyou L. ; Renaudin, V. Datasets and Supporting Materials for the IPIN 2023 Competition Track 4 (Foot-Mounted IMU based Positioning, offsite-online), Zenodo 2023<br> <a href="https://doi.org/10.5281/zenodo.8399764">https://doi.org/10.5281/zenodo.8399764</a></p> <p>Check the citation policy at: <a href="https://doi.org/10.5281/zenodo.8399764">https://doi.org/10.5281/zenodo.8399764</a></p> <p> </p> <p><strong>Contact:</strong><br> For any further questions about the database and this competition track, please contact:</p> <p> Miguel Ortiz (<a href="mailto:miguel.ortiz@univ-eiffel.fr">miguel.ortiz@univ-eiffel.fr</a>) at the University Gustave Eiffel, France.<br> Ni Zhu (<a href="mailto:ni.zhu@univ-eiffel.fr">ni.zhu@univ-eiffel.fr</a>) at the University Gustave Eiffel, France.</p> <p> </p> <p><strong>Acknowledgements:</strong><br> We thank Maximilian Stahlke and Christopher Mutschler at Fraunhofer ISS, as well as Joaquín Torres-Sospedra from Universidade do Minho and Francesco Potortì and Antonino Crivello from ISTI-CNR Pisa, for their support in collecting the datasets.</p> <p>We extend our appreciation to the staff at the Museum for Industrial Culture (Museum Industriekultur) for their unwavering patience and invaluable support throughout our collection days.</p>
Supporting information for "Few-Shot Learning Enables Population-Scale Analysis of Leaf Traits in Populus trichocarpa"
<p>Raw VCF file for <em>Populus trichocarpa</em> V4 SNPs - Biallelic SNP variants were called for 1492 Populus trichocarpa genotypes using GATK Version 4.0 software.</p>
Supporting information for prebiotic triose glycolysis promoted by co-catalytic proline and phosphate in neutral water
<p>Supporting information for prebiotic triose glycolysis promoted by co-catalytic proline and phosphate in neutral water</p>
Direct evidence for atmospheric carbon dioxide removal via enhanced weathering in cropland soil: Supporting data
<p>Datasets (climate, alkalinity, moisture sensors) associated with the manuscript "Direct evidence for atmospheric carbon dioxide removal via enhanced weathering in cropland soil."</p>
Distinct value computations support rapid sequential decisions
<p>This behavioral and modeling data was used and described in the following paper:Mah, A., Schiereck, S.S., Bossio, V., Constantinople, C.M. (2023). Distinct value computations support rapid sequential decisions. Nature Communications.The dataset comprises </p><p>1) Behavioral data for the value-based decision making task in rats, and </p><p>2) computational models fit to the rat behavioral data. </p><p>All files are Matlab data (.mat) files. The code to analyze this data and generate all figures in Mah et al., 2023 is available at {https://github.com/constantinoplelab/published/tree/main/rat_behavior. Data was analyzed using Matlab 2023a with the following additional toolboxes:<br>Curve Fitter<br>Optimization<br>Signal Analyzer</p><p> </p><p>Funding: This work was supported by a K99/R00 Pathway to Independence Award (R00MH111926), an Alfred P. Sloan Fellowship, a Klingenstein-Simons Fellowship in Neuroscience, an NIH Director's New Innovator Award (DP2MH126376), an NSF CAREER Award, R01MH125571, and a McKnight Scholars Award to C.M.C. A.M. was supported by 5T90DA043219 and F31MH130121. A.M. and S.S.S. were supported by 5T32MH019524.</p>
Protocolized Post-Extubation Respiratory Support Study
ClinicalTrials.gov study NCT03288311. IPD Sharing: YES. Countries: 1. Publications: 2.
Study in Primary Care Evaluating Inclisiran Delivery Implementation + Enhanced Support
ClinicalTrials.gov study NCT04807400. IPD Sharing: YES. Countries: 1. Publications: 2.
Everolimus Plus Best Supportive Care vs Placebo Plus Best Supportive Care in the Treatment of Patients With Advanced Neuroendocrine Tumors (GI or Lung Origin)
ClinicalTrials.gov study NCT01524783. IPD Sharing: YES. Countries: 25. Publications: 5.
A Couple Support Intervention for Prostate Cancer
ClinicalTrials.gov study NCT01842438. IPD Sharing: NO. Countries: 1. Publications: 1.
Comparative Effectiveness of Decision Support Strategies for Joint Replacement Surgery
ClinicalTrials.gov study NCT02729831. IPD Sharing: YES. Countries: 1. Publications: 2.
Patient-Centered Reproductive Decision Support Tool for Women Veterans
ClinicalTrials.gov study NCT04584294. IPD Sharing: YES. Countries: 1. Publications: 1.
Evaluation of Medical Cannabis and Prescription Opioid Taper Support for Reduction of Pain and Opioid Dose in Patients With Chronic Non-Cancer Pain
ClinicalTrials.gov study NCT04827992. IPD Sharing: YES. Countries: 1. Publications: 1.
Supporting Tailored And Responsive PrEP in Rural North Carolina
ClinicalTrials.gov study NCT05984030. IPD Sharing: YES. Countries: 1. Publications: 1.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.