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2,322 results for “Circulation”
Defective interferon signaling in the circulating monocytes of type 2 diabetic mice
<h1>Data Repository for scRNA-seq and Cell Communication Analysis in T2DM Stroke Model</h1> <p>This repository contains the data and Seurat/CellChat objects generated for analyzing the transcriptomic response of peripheral monocytes to Type 2 Diabetes Mellitus (T2DM) and ischemic stroke in a mouse model. Data were generated using single-cell RNA sequencing (scRNA-seq), bulk RNA-seq, and analysis with NicheNet and CellChat. This study aims to reveal molecular and cellular changes in diabetic and ischemic conditions, particularly focusing on interferon signaling and inflammation.</p> <h2>Repository Structure</h2> <h3>Root Files</h3> <ul> <li> <p><code>README.md</code>: This file, describing the repository and data files.</p> </li> <li> <p><code>cellchat_object/</code>: Contains RDA files for CellChat analysis.</p> </li> <li> <p><code>scrna_sequencing_raw/</code>: Raw scRNA-seq data files.</p> </li> <li> <p><code>seurat_object/</code>: Contains Seurat objects for clustering and visualization.</p> </li> <li> <p><code>trajectory_object/</code>: Contains Cell Data Set (CDS) objects for trajectory and pseudotime analysis.</p> </li> </ul> <h3>File Descriptions</h3> <h4><code>cellchat_object/</code></h4> <ul> <li> <p><strong>dbdb_case_cellchat.rda</strong>: CellChat object for the db/db mice with ischemic stroke. Analysis was conducted to identify cell-cell communication patterns altered due to stroke in diabetic conditions.</p> </li> <li> <p><strong>dbdb_control_cellchat.rda</strong>: CellChat object for db/db control (no stroke) mice. Provides baseline data for diabetic conditions.</p> </li> <li> <p><strong>dbp_case_cellchat.rda</strong>: CellChat object for the db/+ (normoglycemic) mice with ischemic stroke, representing the stroke model in non-diabetic conditions.</p> </li> <li> <p><strong>dbp_control_cellchat.rda</strong>: CellChat object for db/+ control (no stroke) mice. Baseline for non-diabetic, non-stroke conditions.</p> </li> </ul> <p><strong>Methods</strong>: CellChat analysis identifies ligand-receptor interactions to reveal cross-talk between monocyte subtypes, focusing on pathways affected by T2DM and stroke. These data provide insights into thromboinflammatory responses, interferon signaling, and immune suppression in diabetic mice.</p> <h4><code>scrna_sequencing_raw/</code></h4> <ul> <li> <p><strong>db_db-DMCAO.zip</strong>: Raw scRNA-seq data for db/db mice post-distal middle cerebral artery occlusion (DMCAO).</p> </li> <li> <p><strong>db_db-Sham.zip</strong>: Raw scRNA-seq data for db/db mice with sham surgery (control).</p> </li> <li> <p><strong>db_pos-Sham.zip</strong>: Raw scRNA-seq data for db/+ mice with sham surgery.</p> </li> <li> <p><strong>db_pos-dMCAO.zip</strong>: Raw scRNA-seq data for db/+ mice post-DMCAO.</p> </li> </ul> <p><strong>Methods</strong>: scRNA-seq was performed using 10X Genomics GemCode Technology. Data were processed with Cell Ranger (v1.3), and differential gene expression analysis was conducted in Seurat with normalization based on UMI counts.</p> <h4><code>seurat_object/</code></h4> <ul> <li> <p><strong>bloodstroke.rda</strong>: Seurat object containing processed scRNA-seq data of peripheral blood mononuclear cells (PBMCs) from both diabetic and normoglycemic mice under stroke and sham conditions. Contains cell clusters annotated using SingleR and the ImmGen database.</p> </li> <li> <p><strong>monocytes.rda</strong>: Seurat object specifically for monocytes, enriched through re-clustering in Seurat. Enables focused analysis of monocyte subsets and their responses to diabetic and ischemic conditions.</p> </li> </ul> <p><strong>Methods</strong>: Filtering was performed for cells with fewer than 500 detected genes, and data were normalized using log-normalization. Clustering was carried out with PCA and visualized with UMAP.</p> <h4><code>trajectory_object/</code></h4> <ul> <li> <p><strong>dbdb_control_cds.rda</strong>: Cell Data Set (CDS) object for db/db control monocytes, representing baseline differentiation trajectory under diabetic conditions.</p> </li> <li> <p><strong>dbdb_stroke_cds.rda</strong>: CDS for db/db stroke monocytes, used to observe pseudotime trajectories and differentiation in diabetic and ischemic states.</p> </li> <li> <p><strong>dbp_control_cds.rda</strong>: CDS for db/+ control monocytes, baseline data for normoglycemic mice.</p> </li> <li> <p><strong>dbp_stroke_cds.rda</strong>: CDS for db/+ stroke monocytes, tracking pseudotime trajectory in response to ischemic stroke.</p> </li> <li> <p><strong>monocytes_cds.rda</strong>: CDS focusing on monocyte trajectory across all experimental conditions, facilitating the comparison of diabetic and normoglycemic trajectories.</p> </li> </ul> <p><strong>Methods</strong>: Trajectory analysis was conducted in Monocle 3 to explore cellular differentiation paths. Trajectories reveal potential maturation stages and highlight changes due to T2DM and ischemic conditions.</p> <h2>Methodology Overview</h2> <ol> <li> <p><strong>scRNA-seq and Bulk RNA-seq</strong>: Mononuclear cells were isolated and sequenced using 10X Genomics protocols, with analysis in Seurat to determine cell clusters, particularly monocytes. Bulk RNA-seq was used for pathway validation in broader cell populations.</p> </li> <li> <p><strong>CellChat Analysis</strong>: Ligand-receptor interactions were identified in CellChat, analyzing how cell communication changes with T2DM and stroke. Pathways of interest include the Anxa1-Fpr2 axis for thromboinflammation and MHCII-CD4 for immune activation.</p> </li> <li> <p><strong>Trajectory Analysis</strong>: Using Monocle 3, we investigated monocyte differentiation paths to uncover the effects of T2DM and stroke on cellular progression. Results demonstrate disrupted monocyte differentiation and increased proinflammatory markers in diabetic stroke conditions.</p> </li> <li> <p><strong>NicheNet Analysis</strong>: Identified key ligands affecting monocyte gene expression in diabetic versus non-diabetic conditions, highlighting interferon signaling and inflammatory markers such as Ccl6, Ccl9, and Ifng.</p> </li> </ol> <h2>Notes</h2> <ul> <li> <p>Ensure all analyses respect data filtering thresholds as set in Seurat and Monocle.</p> </li> <li> <p>Refer to the manuscript for further details on experimental setup, animal models, and additional context.</p> </li> </ul> <h2>License</h2> <p>Data and scripts are available for non-commercial use under a Creative Commons License.</p>
Supporting Data for "Radiation-circulation destabilization of ITCZ position in an idealized GCM: Response to hemispherically asymmetric forcing"
<p>Code and netcdf files of processed Isca simulations to reproduce the figures of the submitted manuscript of Timothy M. Merlis, Chiung-Yin Chang, Pablo Zurita-Gotor, and Isaac M. Held (2024): "Radiation-circulation destabilization of ITCZ position in an idealized GCM: Response to hemispherically asymmetric forcing".</p>
Ascorbic acid supports ex vivo generation of plasmacytoid dendritic cells from circulating hematopoietic stem cells: RNA-seq dataset
<p>Plasmacytoid dendritic cells (pDCs) constitute a rare type of immune cell with multifaceted functions, but their potential use as a cell-based immunotherapy is challenged by the scarce cell numbers that can be extracted from blood. Here, we systematically investigate culture parameters for generating pDCs from hematopoietic stem and progenitor cells (HSPCs). Using optimized conditions combined with implementation of HSPC pre-expansion, we generate an average of 465 million HSPC-derived pDCs (HSPC-pDCs) starting from 100,000 cord blood-derived HSPCs. Furthermore, we demonstrate that such protocol allows HSPC-pDC generation from whole blood HSPCs, and these cells display a pDC phenotype and function. Using GMP compliant medium, we observe a remarkable loss of TLR7/9 responses, which is rescued by ascorbic acid supplementation. Ascorbic acid induces transcriptional signatures associated with pDC-specific innate immune pathways suggesting an undescribed role of ascorbic acid for pDC functionality. This constitutes the first protocol for generating pDCs from whole blood, and lay the foundation for investigating HSPC-pDCs for cell-based immunotherapy.</p>
Model data for: Upper-lower layer coupling of recurrent circulation patterns in the Gulf of Mexico
<p>Post processed model output data for "Upper-lower layer coupling of recurrent circulation patterns in the Gulf of Mexico" submitted to Journal of Physical Oceanography. There are two datasets, one for the upper layer (H1) and one for the lower layer (H2). Each one contains the demeaned, detrended, and filtered (Lanczos low-pass) daily fields of layer thickness anomaly to which the authors computed the Hilbert EOFs.</p> <p>File list:</p> <p>H1_GoM_day_ssk15_st30dl.mat - this file contains the layer thickness anomaly fields for the upper layer (<250m)</p> <p>H2_GoM_day_ssk15_st30dl.mat - this file contains the layer thickness anomaly fields for the lower layer (>1000m)</p> <p>Scripts for plotting and processing the data into the model domain are available at:</p> <p>https://github.com/erickolvera/Olvera_et_al_21</p>
data for modeling scale of representation of heterogeneity on simulated salinity and saltwater circulation in coastal aquifers
<p>This is the modeling data for modeling scale of representation of heterogeneity on simulated salinity and saltwater circulation in coastal aquifers. We setup a series of SEAWAT models to see the scale-dependent heterogeneity in simulations of saltwater circulation and cautions</p>
Data for "Machine Learning Parameterization of Subgrid-Scale Orographic Gravity Wave Drag in a Middle-Atmosphere General Circulation Model" by Lu et al., submitted to JAMES, 2022.
<p>The NetCDF data file involving the decision tree strucutre attributes of the random forest emulator.</p> <p>gcm_regressors/<br> The data file involving the decision tree strucutre attributes (in NetCDF format)</p>
NICAM AMIP-type simulation data for the article "Deceleration of Madden–Julian Oscillation Speed in NICAM AMIP-type Simulation Associated with Biases in the Walker Circulation Strength"
<p>This data set includes data from 30-year integration on nonhydrostatic icosahedral atmospheric model (NICAM) following an atmospheric model intercomparison project (AMIP) protocol with a slab ocean model from 1 June 1978 to 6 January 2009 (c.f. Kodama et al. 2015), and their GrADs description ctl files. All outputs are daily averages on 2.5 x 2.5 degrees resolution. Output variables are outgoing longwave radiation (W m<sup>-2</sup>), skin temperature (K), sea surface temperature (K), and zonal wind (m s<sup>-1</sup>) on pressure levels.</p>
Uncertainty quantification in cerebral circulation simulations focusing on the collateral flow: Surrogate model approach with machine learning
<p>Data and code underlying the findings reported in the paper titled "Uncertainty quantification in cerebral circulation simulations focusing on the collateral flow: Surrogate model approach with machine learning."</p>
Precipitation efficiency amplifies climate sensitivity by enhancing tropical circulation slowdown and Eastern Pacific warming pattern
<p class="MsoNormal"><span>Cloud processes are the largest source of uncertainty in quantifying the global temperature response to CO<sub>2</sub> rise. Still, the role of precipitation efficiency (PE) – surface rain per unit column-integrated condensation – is yet to be quantified. Here we use 36 limited-domain cloud resolving simulations from the Radiative-Convective Equilibrium Model Intercomparison Project to show that they strongly imply climate warming will result in increases to net precipitation efficiency. We then analyze 35 General Circulation Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 and find that increasing PE enhances tropical circulation slowdown and strengthens eastern equatorial Pacific warming. These changes trigger pan-tropical positive cloud feedback by causing stratiform anvil cloud reduction and stratocumulus suppression, and thereby amplify overall climate sensitivity. Quantitatively, we find that in the 24 of 35 GCMs which match the cloud-resolving models in simulating increasing PE with greenhouse warming, mean Effective Climate Sensitivity is 1 K higher than in GCMs in which PE decreases. The models simulating increasing PE also comprise all estimates of effective climate sensitivity over 4 K. Taken together, these results show that further constraining PE sensitivity to warming will reduce uncertainty over future climate change.</span></p>
Gravity Wave Morphology During the 2018 Sudden Stratospheric Warming Simulated by a Whole Neutral Atmosphere General Circulation Model
<p>This dataset includes a complete set of raw data, metadata and saved session data which is necessary for re-producing figures in a paper entitled "Gravity Wave Morphology During the 2018 Sudden Stratospheric Warming Simulated by a Whole Neutral Atmosphere General Circulation Model" submitted to the Journal of Geophysical Research - Atmosphere.</p>
Supplementary Information - Circulating insulin-like growth factor system adaptations in hibernating brown bears indicate increased tissue IGF availability
<p>Supplementary figures and tables for the manuscript entitled “Circulating insulin-like growth factor system adaptations in hibernating brown bears indicate increased tissue IGF availability”.</p>
Tidal triggering of seismic swarm associated with hydrothermal circulation at Blanco Ridge Transform Fault Zone in northeast Pacific
<p>Supplementary Information</p> <p>for</p> <p>Tidal triggering of seismic swarm associated with hydrothermal circulation at Blanco Ridge Transform Fault Zone in northeast Pacific</p>
Ensembled projection outputs of Lake Sunapee using multiple General Circulation models and Lake models
<p>This dataset contains the ensemble projection output of Lake Sunapee, NH. The conception and methods of the dataset is explained in the manuscript "Uncertainty in projections of future lake thermal dynamics is differentially driven by global climate models and lake models."</p>
Transposon DNA sequences facilitate the tissue-specific gene transfer of circulating tumor DNA between human cells
<p><strong><span>nuc_ctDNA_process</span></strong></p> <p><span>ImageJ 1.x macros and Matlab code for processing 3D nuclear classification and quantification. This repo is designed to help you recreate the methods use in the associated publication. Please don't hesitate to contact if you have questions. Happy to debug, update, etc if there's need.</span></p> <p><strong><span>Lif files:</span></strong></p> <p><span>Use ImageJ 1.x macro in fiji folder to process lif files for subsequent ilastik and Matlab processing. Works with 3 channel data (DAPI, DIC, Rh-Red-X) and 4 channel data (DAPI, Cy5, Rh-Red-X, DIC). Generates .h5 or .tif files for ilastik raining, .jpgs for visualization and ROI overlays, and raw tif files for Matlab analysis.</span></p> <p><strong><span>Macro Usage</span></strong></p> <p><span>Drag and drop; click Run and select .lif of interest. Only 3D data will be included, single layer images will be noted in output. A table of dimensions and max intensities is also created. Save .csv image info, and .txt output log for reference.</span></p> <p><strong><span>Organize Folder Structure</span></strong></p> <p><span>Folders: </span></p> <ul> <li><span>Ilastik output</span></li> <li><span>Nuc</span></li> <li><span>Raw</span></li> <li><span>Roi</span></li> </ul> <p><span> ------------</span></p> <ul> <li><span>Place .h5 nuclear, or .tif nuclear and DIC, and .jpg thumbnail data in subfolder called “nuc”</span></li> <li><span>Place .tif raw data export into subfolder called “raw”</span></li> <li><span>Create subfolders “ilastik output” and “roi”</span></li> <li><span>Ilastik (version 1.3.2post1) trained with ~10-20% of datasets </span></li> <ul> <li><span>Ilastik side note: currently don't know how to share Ilastik projects without getting errors on loading for the given files and filepaths present during creation. You will need to train your own models. See NoPhotonLeftBehind for Ilastik series that includes training tips and details of features used for these data. <a href="https://www.youtube.com/channel/UCRVa5DSphB5gHMaFKPgyKSQ"><span>https://www.youtube.com/channel/UCRVa5DSphB5gHMaFKPgyKSQ</span></a></span></li> </ul> <li><span>Models trained as Pixel Classifications – two classes, background and nucleus</span></li> <li><span>Ilsatik model trained to classify nuclear vs non nuclear – classical thresholding methods found to be less effective due to varying amounts on cytoplasmic DNA stain present.</span></li> <li><span>Single match and mismatch trained using nuclear channel only; double mismatch trained using nuclear and DIC channels together</span></li> <li><span>Data separated and models trained for each cell type due to distinct morphologies, e.g. MM1S model, HCT116 model, etc etc</span></li> <li><span>Probability density files </span></li> <ul> <li><span>Matlab looks for “*_nrmNuc.tiff“ in relative folder “.\ilastik output”, and this is the suffix added in the Fiji macro</span></li> <li><span>In ilastik, set output format to multipage tiff, and select path to .{nickname}.tiff. Note, use path of .{nickname}_nrmNuc.tiff if _nrmNuc is not added during your file collation and logistics to this point. Also note .tiff not .tif</span></li> <li><span>Leave image export settings as default; shape here is, for example, 16, 512, 512, 1, with axis order zyxc and data type float32</span></li> <li><span>In Batch Processing section, select all of the .h5 or .tif files in the “nuc” folder and Process all files</span></li> </ul> <li><span>Matlab UI </span></li> <ul> <li><span>Files Tab: </span></li> <ul> <li><span>Set Root – select folder containing “ilastik output”, “raw”, “roi”, and “nuc”</span></li> <li><span>Filename list will propagate, and Overview text at the top will highlight red if the correct number of files are not present in all folders. (TODO: - run test on error scenario to get instructions)</span></li> <li><span>Sig Num Chns – the total number of channels in the raw data tif files</span></li> <li><span>Rh/Cy5 Sig Chn – the 1 to N based index of the channel to measure inside the nucleus</span></li> <li><span>Rh/Cy5 Bkgd – the number of counts considered as background/cell autoflourescene/non-specific signal during measurements; only voxels with counts above this level will be included in the measurements</span></li> <li><span>ROI Num Chns – total number of channels in the ilastik probability density tiff files</span></li> <li><span>ROI Chn – 1 to N based index of channel to use for generating nuclear 3D ROIs</span></li> <li><span>Thumbnails on/off toggle when selecting images in list</span></li> <li><span>Currently only single or double channel analyses available (signal is measured inside and outside of nucleus 3D ROI)</span></li> <li><span>Click on files to view the nuc jpgs. Click Processing tab to experiment with settings. Note, above channel totals and indices do not currently have error checking. Check correct combinations if you receive tif read errors. Jpgs are loaded on each click, and raw is loaded on switching to Processing tab; expect short delay depending on file size and available disk read speeds.</span></li> <li><span>Open in Explorer button – no prizes for guessing that it opens the selected file in explorer. It defaults to the raw data.</span></li> <li><span>Process All button runs all the files using the settings in place in the Processing Tab. </span></li> <ul> <li><span>A dated folder in roi is created. Inside this folder there are four different types of output file:</span></li> </ul> </ul> <li><span>.bin – a binary mask of the 3D ROI</span></li> <li><span>_dims.bin – the dimensions of the binary mask</span></li> <li><span>.jpg – a thumbnail of ROI overlays</span></li> <li><span>.mat – parameters used for generating the ROIs (open .mat files, and click on the params variable in the Import Wizard to quickly view the relevant parameters) </span></li> <ul> <li><span>Use Masks dropdown: </span></li> <ul> <li><span>For faster re-processing of data with differing minimum number of voxels existing binary masks can be used</span></li> <li><span>Note, resulting .mat file in subsequent output will not reflect the parameters used to generate the binary masks – refer to the original folder (this is noted and will be added to newer versions)</span></li> </ul> <li><span> </span></li> </ul> <li><span>Processing tab: </span></li> <ul> <li><span>FFT % is the amount of Fourier space to keep; lower values retain low frequencies only – empirically determined for best resulting nuclear shape</span></li> <li><span>FFT Smooth value is Gaussian smoothing value in pixels applied to the ellipsoid mask used to retain the central region of Fourier space. Ringing can be seen for values close to 0, increase as needed.</span></li> <li><span>Gauss Smooth is the Gaussian smoothing applied to the raw prob data prior to Otsu thresholding. In noisy classifications thresholding leads to multiple fragmented regions; some smoothing prior to thresholding helps to ‘fuse’ these fragmented regions, prior to 3D FFT spatial filtering to smooth based on size.</span></li> <li><span>FFT xz factor is used to avoid smoothing nuclei in the z direction more than x and y. This value affects the ratio of xy and z of the 3D ellipsoid used to mask Fourier space. Set empirically; Click Run and then View Volume to inspect the z ‘stretch’.</span></li> <li><span>Button group options to apply different combinations of smoothing and FFT spatial filters: </span></li> <ul> <li><span>Gauss – uses Gauss Smooth value above; applied to raw prob data</span></li> <li><span>Otsu – Otsu binary threshold</span></li> <li><span>Fill – Binary fill applied after smooth and binarization</span></li> <li><span>FFT – 3D spatial filtering based on % of Fourier space</span></li> </ul> <li><span>Run, well, runs the analysis</span></li> <li><span>View Volume displays 3D viewer for resulting data set</span></li> <li><span>Min volume slider and value are used to exclude all 3D ROIs smaller than specified value; in voxels. Note slider is linear and plot is log.</span></li> </ul> <li><span>Notes: </span></li> <ul> <li><span>Requires Matlab 2018a or newer</span></li> <li><span>Requires Parallel Computing Toolbox for parfor loop in function ProcessAllButtonPushed. Change parfor to for if not available.</span></li> <li><span> </span></li> </ul> </ul> <li><span>Matlab filelist: </span></li> <ul> <li><span>*.mlapp</span></li> <li><span>import_tif.m</span></li> <li><span>bw_outline_p.m</span></li> <li><span>smth_otsu_fill_p.m</span></li> <li><span>LPFFT3D_p.m</span></li> <li><span>otsu_bw.m</span></li> <li><span>makepsd3.m</span></li> <li><span>ellipsoid_mask.m</span></li> <li><span>bin_load_mask.m</span></li> <li><span>process_ctDNA_table.m</span></li> <li><span>_p refers to passed param struct: </span></li> <ul> <li><span>wid = 3; % width of dilation in outline overlay</span></li> <li><span>pc; % percent of Fourier space to keep - smaller numbers -> more blurred out larger images</span></li> <li><span>pad = 1; % pad Fourier space to the next power of 2</span></li> <li><span>umpx = 0.09; % image pix size</span></li> <li><span>umpz = 0.3; % again in z</span></li> <li><span>fft_smth; % smoothing of the eliptical Fourier space mask</span></li> <li><span>gauss_smth; % sigma of Guass smooth for Guass, Otsu, Fill, BW</span></li> <li><span>scl = [1 1 1/0.3]; % scale ratios for volume viewer</span></li> <li><span>fft_xz_factor; % factor to increase or decrease the amount of z FFT smoothing compared to xy</span></li> <li><span>minvol = 0;</span></li> </ul> </ul> </ul>
Salvage circulation of 5mC from calf DNA into new synthetic DNA
<p><strong>ABSTRACT</strong></p> <p>We investigated the salvage pathway of 5-methyl cytosine (5mC), a nucleotide modification crucial for epigenetic regulation, utilizing a mimicked natural pathway protocol. DNA hydrolysis revealed the presence of dCMP with 5mC modification (5mdCMP) in calf DNA, suggesting its potential recycling to the nucleotide pool. Phosphorylation experiments demonstrated the conversion of 5mdCMP to 5mdCTP, highlighting the feasibility of its salvage pathway. Nanopore sequencing confirmed the incorporation of salvaged 5mC into newly synthesized DNA strands. Additionally, protein expression assays revealed downregulation in the presence of salvaged 5mC, indicating its impact on gene expression. Our findings underscore the importance of the salvage pathway for 5mC and its implications for epigenetic regulation and disease. Further research is necessary to elucidate the mechanisms and consequences of 5mC salvage fully.</p>
cGENIE model experiment results for 'Sensitivity of ocean circulation to warming during the Early Eocene greenhouse'
Open the record for dataset details and reuse information.
Model output for: "Freshwater input from glacier melt outside Greenland alters modeled northern high-latitude ocean circulation"
<p>NEMO-ANHA4 and OGGM model output files used in the article: "Freshwater input from glacier melt outside Greenland alters modeled northern high-latitude ocean circulation".</p> <p> </p> <p>halfsolid.zip and noOGGM.zip contain output of the runs called <em>halfsolid</em> and <em>noOGGM</em> in the article. output_data_OGGM.zip contains the output files of OGGM runs.</p>
Data for "Impacts of an active Pacific Meridional Overturning Circulation on the Pliocene climate and hydrological cycle"
<p>Post-Processing Scripts and Data for the Paper<br>Title: Impacts of an Active Pacific Meridional Overturning Circulation on the Pliocene Climate and Hydrological Cycle<br>Authors: Minmin Fu, Alexey Fedorov<br>Publication Year: 2024<br>Contact: minmin.fu@yale.edu</p> <p>Overview<br>This repository contains the post-processing scripts and data used in the paper. It includes Jupyter notebooks for data analysis and plot generation, as well as the GCM output and utilities for adding land-sea masks and proxy sites.</p> <p>Repository Structure<br>notebooks/: Jupyter notebooks for analyzing data and creating plots.<br>data/: GCM output files for reproducing all figures in the paper.<br>utilities/: Functions for adding the land-sea mask and proxy sites.<br>PlioMIP2/: PlioMIP2 boundary conditions.</p> <p>Data<br>The data directory contains the GCM output files necessary for reproducing all figures. Ensure you have the necessary storage space as these files may be large.</p> <p>Utilities<br>The utilities directory contains utility functions, including:</p> <p>Land-Sea Mask Functions: Scripts to apply land-sea masks to the data.<br>Proxy Site Functions: Scripts to integrate proxy site data into the analysis.<br>The PlioMIP2 directory contains the boundary condition files used for the PlioMIP2 experiments.</p>
Pacific Walker Circulation modulated millennial-scale Asian monsoon rainfall variability over past 40 kyr
Open the record for dataset details and reuse information.
Forward in time particle-tracking simulation in the Kuroshio Extension re-circulation gyre in 2019 using GLORYS12
<p>Tracers were released at the targeted mesoscale eddy in September 03 2019, and their surface transport was modeled for the the forward two months. Units are expressed as the number of tracer particles in each glid of 1/12° horizontal resolution. The color shades indicate the number of particles. The particle number 50 indicates that the number of particles in a grid is 50 or more.</p>
ScienceDex guides
Understand access before you commit
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.