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293 results for “protein kinase”
Classifying protein kinase conformations with machine learning: data
<p>This data collection accompanies the manuscript "Classifying protein kinase conformations with machine learning".</p> <p>It is created using the <a href="https://github.com/edikedik/kinactive">kinactive</a> v0.1 tool written in pure Python v3.10. <strong>Note that the data are provided for the reference and reproducibility purposes and will not be compatible with later versions of `kinactive` built upon <a href="https://github.com/edikedik/lXtractor">lXtractor</a> > 0.1.1.</strong> Refer to the <a href="https://kinactive.readthedocs.io/en/latest/index.html">kinactive documentation</a> for instructions on how to obtain an actualized version of the structural kinome collection.</p> <p>File descriptions:</p> <ul> <li>db_v3.tar.gz -- a structural kinome collection archive. One can unpack it and inspect the contents or load it into the Python interpreter using `kinactive` or `lXtractor` tools.</li> <li>db_af2.tar.gz -- an AlphaFold2 kinome collection for Swiss-Prot sequences.</li> <li>default_*_vs.tsv -- structure/sequence variables calculated with lXtractor and used in an interpretable ML pipeline.</li> <li>*_features.tsv -- lists of ranked features selected by the <a href="https://github.com/edikedik/eBoruta">eBoruta</a> tool for each classifier.</li> <li>Supplement_labels.tsv -- ML model predictions for each PK domain structure found in db_v3.</li> <li>predictions_af2.csv -- Active/Inactive and DFG labels predicted for domains in db_af2.</li> </ul> <p> </p>
Regulatory spine RS3 residue of protein kinases: a lipophilic bystander or a decisive element in the small-molecule kinase inhibitor binding?
<p>Datasets related to publication: </p> <p>Shevchenko E, Pantsar T: Regulatory spine RS3 residue of protein kinases: a lipophilic bystander or a decisive element in the small-molecule kinase inhibitor binding?. <em><em>Biochem Soc Trans</em></em> 28 February 2022; 50 (1): 633–648</p> <p>https://doi.org/10.1042/bst20210837</p> <p> </p> <p> </p>
Tyrosine-protein kinase Yes controls endothelial junctional plasticity and barrier integrity by regulating VE-cadherin phosphorylation and endocytosis
<p><strong>Abstract</strong></p> <p>Vascular endothelial (VE)-cadherin in endothelial adherens junctions is an essential component of the vascular barrier, critical for tissue homeostasis and implicated in diseases such as cancer and retinopathies. Inhibitors of Src cytoplasmic tyrosine kinase have been applied to suppress VE-cadherin tyrosine phosphorylation and prevent excessive leakage, edema and high interstitial pressure. Here we show that the Src-related Yes tyrosine kinase, rather than Src, is localized at endothelial cell (EC) junctions where it becomes activated in a flow-dependent manner. EC-specific <em>Yes1</em> deletion suppresses VE-cadherin phosphorylation and arrests VE-cadherin at EC junctions. This is accompanied by loss of EC collective migration and exaggerated agonist-induced macromolecular leakage. Overexpression of <em>Yes1</em> causes ectopic VE-cadherin phosphorylation, while vascular leakage is unaffected. In contrast, in EC-specific Src-deficiency, VE-cadherin internalization is maintained, and leakage is suppressed. In conclusion, Yes-mediated phosphorylation regulates constitutive VE-cadherin turnover, thereby maintaining endothelial junction plasticity and vascular integrity.</p> <p><strong>Method for retinal EC distribution analysis</strong></p> <p>Chimeric recombination was induced in iSuRe-Cre+ mice at P3 by i.p. injection of tamoxifen (100 µg/mouse, Sigma). Retinas were taken at P7 and P15, immunostained for CD31 and flat-mounted. Images were taken by z-stack tile scanning using a 10X objective on a confocal microscope (Leica SP8). Maximum intensity projection images of whole retinas were used for image segmentation, which was performed with ImageJ resources. The maximum projection of the MbTomato channel threshold was established to distinguish MbTomato+ cells from the background. Outliers with a radius between 0.2-1.0 µm were removed. The CD31 channel (after maximum projection) was used to define the outlines of veins and arteries; the optic nerve was used as a mask to define a referential system. For computational analysis, a bespoken Python-based workflow was employed, accessible on GitHub (https://github.com/wgiese/retina-vein-artery-cs). For every pixel in the image, three numbers were computed (using the mask as referential): (1) distance to the nearest vein (d<sub>v</sub>), (2) distance to the nearest artery (d<sub>a</sub>) and (3) radial distance to the optic nerve (r). From these measures, the relative distances by ϕ<sub>v-a</sub> = d<sub>v/</sub>(d<sub>v</sub> + d<sub>a</sub>) were obtained. The EC distribution was computed by performing the operation for all YFP-positive pixels, which were used as a proxy for EC distribution. A kernel density estimation was used to approximate the underlying EC distribution in the 2D coordinate system spanned by ϕ<sub>v-a</sub> and r. </p>
Stimulation of the catalytic activity of the tyrosine kinase Btk by the adaptor protein Grb2: Part 2
<p>The Tec-family kinase Btk contains a lipid-binding Pleckstrin homology and Tec homology (PH-TH) module connected by a proline-rich linker to a "Src module", an SH3-SH2-kinase unit also found in Src-family kinases and Abl. We showed previously that Btk is activated by PH-TH dimerization, which is triggered on membranes by the phosphatidyl inositol phosphate PIP<sub>3</sub>, or in solution by inositol hexakisphosphate (IP<sub>6</sub>) (Wang <em>et al.</em> 2015, https://doi.org/10.7554/eLife.06074). We now report that the ubiquitous adaptor protein growth-factor-receptor-bound protein 2 (Grb2) binds to and substantially increases the activity of PIP<sub>3</sub>-bound Btk on membranes. Using reconstitution on supported-lipid bilayers, we find that Grb2 can be recruited to membrane-bound Btk through interaction with the proline-rich linker in Btk. This interaction requires intact Grb2, containing both SH3 domains and the SH2 domain, but does not require that the SH2 domain be able to bind phosphorylated tyrosine residues – thus Grb2 bound to Btk is free to interact with scaffold proteins via the SH2 domain. We show that the Grb2-Btk interaction recruits Btk to scaffold-mediated signaling clusters in reconstituted membranes. Our findings indicate that PIP<sub>3</sub>-mediated dimerization of Btk does not fully activate Btk, and that Btk adopts an autoinhibited state at the membrane that is released by Grb2.</p>
Stimulation of the catalytic activity of the tyrosine kinase Btk by the adaptor protein Grb2: Part 3
The Tec-family kinase Btk contains a lipid-binding Pleckstrin homology and Tec homology (PH-TH) module connected by a proline-rich linker to a "Src module", an SH3-SH2-kinase unit also found in Src-family kinases and Abl. We showed previously that Btk is activated by PH-TH dimerization, which is triggered on membranes by the phosphatidyl inositol phosphate PIP<sub>3</sub>, or in solution by inositol hexakisphosphate (IP<sub>6</sub>) (Wang <em>et al.</em> 2015, https://doi.org/10.7554/eLife.06074). We now report that the ubiquitous adaptor protein growth-factor-receptor-bound protein 2 (Grb2) binds to and substantially increases the activity of PIP<sub>3</sub>-bound Btk on membranes. Using reconstitution on supported-lipid bilayers, we find that Grb2 can be recruited to membrane-bound Btk through interaction with the proline-rich linker in Btk. This interaction requires intact Grb2, containing both SH3 domains and the SH2 domain, but does not require that the SH2 domain be able to bind phosphorylated tyrosine residues – thus Grb2 bound to Btk is free to interact with scaffold proteins via the SH2 domain. We show that the Grb2-Btk interaction recruits Btk to scaffold-mediated signaling clusters in reconstituted membranes. Our findings indicate that PIP<sub>3</sub>-mediated dimerization of Btk does not fully activate Btk, and that Btk adopts an autoinhibited state at the membrane that is released by Grb2.
Stimulation of the catalytic activity of the tyrosine kinase Btk by the adaptor protein Grb2: Part 1
The Tec-family kinase Btk contains a lipid-binding Pleckstrin homology and Tec homology (PH-TH) module connected by a proline-rich linker to a "Src module", an SH3-SH2-kinase unit also found in Src-family kinases and Abl. We showed previously that Btk is activated by PH-TH dimerization, which is triggered on membranes by the phosphatidyl inositol phosphate PIP<sub>3</sub>, or in solution by inositol hexakisphosphate (IP<sub>6</sub>) (Wang <em>et al.</em> 2015, https://doi.org/10.7554/eLife.06074). We now report that the ubiquitous adaptor protein growth-factor-receptor-bound protein 2 (Grb2) binds to and substantially increases the activity of PIP<sub>3</sub>-bound Btk on membranes. Using reconstitution on supported-lipid bilayers, we find that Grb2 can be recruited to membrane-bound Btk through interaction with the proline-rich linker in Btk. This interaction requires intact Grb2, containing both SH3 domains and the SH2 domain, but does not require that the SH2 domain be able to bind phosphorylated tyrosine residues – thus Grb2 bound to Btk is free to interact with scaffold proteins via the SH2 domain. We show that the Grb2-Btk interaction recruits Btk to scaffold-mediated signaling clusters in reconstituted membranes. Our findings indicate that PIP<sub>3</sub>-mediated dimerization of Btk does not fully activate Btk, and that Btk adopts an autoinhibited state at the membrane that is released by Grb2.
Predicted models of S receptor kinase ectodomain (eSRK), S-locus protein 11 (SP11), and eSRK-SP11 complexes
<p>Predicted models of <em>S</em> receptor kinase ectodomain (eSRK), <em>S</em>-locus protein 11 (SP11), and their complexes using ColabFold and curated multiple sequence alignments (MSAs).</p> <p> </p>
Stimulation of the catalytic activity of the tyrosine kinase Btk by the adaptor protein Grb2: Part 1
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Stimulation of the catalytic activity of the tyrosine kinase Btk by the adaptor protein Grb2: Part 2
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Stimulation of the catalytic activity of the tyrosine kinase Btk by the adaptor protein Grb2: Part 3
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Crystal structure of the tandem kinase & triphosphate tunnel metalloenzyme domain module of the TTM1 protein from Arabidoposis thaliana in complex with inorganic phosphate and citric acid - 3lambda SeMAD dataset
<p>bzip2ed tar archive containing the diffraction images (Pilatus 2M-F detector, SLS beamline PXIII, collected on 19.12.2016) for 3 wavelength Se MAD experiment (infl, inflection point, peak, peak, rem, high energy remote) and the associated data processing files (xds_inf, xds_peak, xds_rem) </p>
Crystal structure of the tandem kinase & triphosphate tunnel metalloenzyme domain module of the TTM1 protein from Arabidoposis thaliana in complex with an adenosine nucleotide analog.
<p>bzip2ed tar archive containing the diffraction images (Pilatus 2M-F detector, SLS beamline PXIII, collected on 19.12.2016) and the associated data processing files (xds) </p>
Crystal structure of the tandem kinase & triphosphate tunnel metalloenzyme domain module of the TTM1 protein from Arabidoposis thaliana in complex with inorganic phosphate and citric acid - native dataset
<p>bzip2ed tar archive containing the diffraction images (Pilatus 2M-F detector, SLS beamline PXIII, collected on 19.12.2016) and the associated data processing files (xds) </p>
How can we biochemically validate protein function predictions with the deoxycytidine kinase family? - Associated data
<p>This is the data that accompanies the pub "<a href="https://doi.org/10.57844/arcadia-1e5d-e272">How can we biochemically validate ProteinCartography with the deoxycytydine kinase family?</a>" It's part of a group of pubs focused on validating ProtienCartography that begins with "<a href="https://doi.org/10.57844/arcadia-cae9-96c4">A strategy to validate protein functions <em>in vitro</em></a><a href="https://doi.org/10.57844/arcadia-cae9-96c4">." </a></p> <p>For this repository, we ran ProteinCartography <a href="https://github.com/Arcadia-Science/ProteinCartography/releases/tag/v0.5.0">v0.5.0</a> on the deoxycytidine kinase (dCK) using human dCK as our input (UniProt ID: <a href="https://www.uniprot.org/uniprotkb/P27707/entry">P27707</a>). We asked for 3,000 Foldseek hits and 7,000 BLAST hits for a total of 10,000 structures. The updated configuration file is in the zipped folder in this repository. Also included in the zipped folder are the inputs, structures of all hits, and all ProteinCartography results. </p> <p>Finally, we created a custom overlay for the protein map using this <a href="https://github.com/Arcadia-Science/2023-actin-embedding/blob/main/notebooks/3_plotting_overlays.ipynb">notebook</a> and the manually annotated TSV file in this repository, where we denoted which group of substrates a protein is predicted to act on based on its annotation from UniProt.</p>
Conduction in the Right and Left Ventricle is Differentially Regulated by Protein Kinases and Phosphatases: Implications for Arrhythmogenesis
<p>Movies of paced activation and of arrhythmia acquired during perfusion of isolated rabbit hearts with CaMKII inhibitor KN93 or PKA inhibitor H89</p>
Data file with manuscript titled 'A Structurally Validated Sequence Alignment of 497 Human Protein Kinase Domains'
<p>The files used in different analysis reported in the manuscript titled - 'A Structurally-Validated Multiple Sequence Alignment of 497 Human Protein Kinase Domains' are shared at two locations. Following is a brief description of these files.</p> <p>Location - https://github.com/DunbrackLab/Kinases<br> 1. HMM profile files - HMM files for each of the nine groups computed separately labeled as Groupname.hmm, like AGC.hmm<br> 2. HMM profile file - HMM file computed from the full alignment including all the sequences - Human-PK.hmm<br> 3. Score files - HMM scores of each kinase sequence against all the groupwise HMMs both for iteration1 (HMM-iter1-scores-tables.txt) and iteration2 (HMM-iter1-scores-tables.txt)<br> 4. Jalview session file - Kinase alignment with sequences colored by secondary structure information from PDB file if the structure is known; or predicted secondary structure if the experimental structure is not known. The file could be opened in Jalview - kinases-PDB-SSPred.jvp</p> <p>Location - https://zenodo.org/record/3445533<br> 1. The file contains list of residue pairs aligned in pairwise structural alignments of 272 human protein kinases which were used as a benchmark in the study. The alignments were created by FATCAT and optimized by SE program.</p>
Dataset (VII) related to publication: Decisive Role of Water and Protein Dynamics in Residence Time of p38a MAP Kinase Inhibitors
<p>MD simulation data of compound <strong>1</strong> in MSM <strong>2-<em>S</em><sub>3</sub></strong> conformations of the related to the publication Pantsar et al.: <em>Decisive Role of Water and Protein Dynamics in Residence Time of p38a MAP Kinase Inhibitors.</em></p> <p>Individual .zip files contain raw-desmond trajectories (-out.cms files and trj-files).</p> <p>All datasets related to this publication:</p> <p><a href="https://doi.org/10.5281/zenodo.4568113">https://doi.org/10.5281/zenodo.4568113</a>(compound <strong>1</strong>; dataset: I)</p> <p><a href="https://doi.org/10.5281/zenodo.4572444">https://doi.org/10.5281/zenodo.4572444</a> (compound <strong>1</strong>; dataset: II)</p> <p><a href="https://doi.org/10.5281/zenodo.4561797">https://doi.org/10.5281/zenodo.4561797</a>(compound <strong>2</strong>; dataset: III)</p> <p><a href="https://doi.org/10.5281/zenodo.4563896">https://doi.org/10.5281/zenodo.4563896</a> (compound <strong>2</strong>; dataset: IV)</p> <p><a href="https://doi.org/10.5281/zenodo.5563359">https://doi.org/10.5281/zenodo.5563359</a> (<strong>SB203580</strong>; dataset: V)</p> <p><a href="https://doi.org/10.5281/zenodo.5563655">https://doi.org/10.5281/zenodo.5563655</a> (<strong>SB203580</strong>; dataset: VI)</p> <p><a href="https://doi.org/10.5281/zenodo.5564118%20">https://doi.org/10.5281/zenodo.5564118 </a>(compound <strong>1</strong> simulated in compound <strong>2</strong> metastable state <strong>2-<em>S</em><sub>3</sub></strong>; dataset: VII)</p> <p><a href="https://doi.org/10.5281/zenodo.5564208%20">https://doi.org/10.5281/zenodo.5564208 </a>(compound <strong>1</strong> simulated in compound <strong>2</strong> metastable state <strong>2-<em>S</em><sub>3</sub></strong>; dataset: VIII)</p> <p><a href="https://doi.org/10.5281/zenodo.5564586">https://doi.org/10.5281/zenodo.5564586</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: IX)</p> <p><a href="https://doi.org/10.5281/zenodo.5570882">https://doi.org/10.5281/zenodo.5570882</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: X)</p> <p><a href="https://doi.org/10.5281/zenodo.5571352">https://doi.org/10.5281/zenodo.5571352</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: XI)</p> <p>The datasets include original Desmond raw-trajectories (datasets I–VIII), PDB-coordinates for the energy minimized metastable state derived structures (datasets II, IV and VI) and raw-trajectories of the well-tempered metadynamics simulations (dataset IX–XI).</p>
Dataset (VIII) related to publication: Decisive Role of Water and Protein Dynamics in Residence Time of p38a MAP Kinase Inhibitors
<p>MD simulation data of compound <strong>1</strong> in MSM <strong>2-<em>S</em><sub>3</sub></strong> conformations of the related to the publication Pantsar et al.: <em>Decisive Role of Water and Protein Dynamics in Residence Time of p38a MAP Kinase Inhibitors.</em></p> <p>Individual .zip files contain raw-desmond trajectories (-out.cms files and trj-files).</p> <p>All datasets related to this publication:</p> <p><a href="https://doi.org/10.5281/zenodo.4568113">https://doi.org/10.5281/zenodo.4568113</a>(compound <strong>1</strong>; dataset: I)</p> <p><a href="https://doi.org/10.5281/zenodo.4572444">https://doi.org/10.5281/zenodo.4572444</a> (compound <strong>1</strong>; dataset: II)</p> <p><a href="https://doi.org/10.5281/zenodo.4561797">https://doi.org/10.5281/zenodo.4561797</a>(compound <strong>2</strong>; dataset: III)</p> <p><a href="https://doi.org/10.5281/zenodo.4563896">https://doi.org/10.5281/zenodo.4563896</a> (compound <strong>2</strong>; dataset: IV)</p> <p><a href="https://doi.org/10.5281/zenodo.5563359">https://doi.org/10.5281/zenodo.5563359</a> (<strong>SB203580</strong>; dataset: V)</p> <p><a href="https://doi.org/10.5281/zenodo.5563655">https://doi.org/10.5281/zenodo.5563655</a> (<strong>SB203580</strong>; dataset: VI)</p> <p><a href="https://doi.org/10.5281/zenodo.5564118%20">https://doi.org/10.5281/zenodo.5564118 </a>(compound <strong>1</strong> simulated in compound <strong>2</strong> metastable state <strong>2-<em>S</em><sub>3</sub></strong>; dataset: VII)</p> <p><a href="https://doi.org/10.5281/zenodo.5564208%20">https://doi.org/10.5281/zenodo.5564208 </a>(compound <strong>1</strong> simulated in compound <strong>2</strong> metastable state <strong>2-<em>S</em><sub>3</sub></strong>; dataset: VIII)</p> <p><a href="https://doi.org/10.5281/zenodo.5564586">https://doi.org/10.5281/zenodo.5564586</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: IX)</p> <p><a href="https://doi.org/10.5281/zenodo.5570882">https://doi.org/10.5281/zenodo.5570882</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: X)</p> <p><a href="https://doi.org/10.5281/zenodo.5571352">https://doi.org/10.5281/zenodo.5571352</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: XI)</p> <p>The datasets include original Desmond raw-trajectories (datasets I–VIII), PDB-coordinates for the energy minimized metastable state derived structures (datasets II, IV and VI) and raw-trajectories of the well-tempered metadynamics simulations (dataset IX–XI).</p>
Dataset (V) related to publication: Decisive Role of Water and Protein Dynamics in Residence Time of p38a MAP Kinase Inhibitors
<p>MD simulation data of <strong>SB203580</strong> related to the publication Pantsar et al.: <em>Decisive Role of Water and Protein Dynamics in Residence Time of p38a MAP Kinase Inhibitors.</em></p> <p>Individual .zip files contain raw-desmond trajectories (-out.cms files and trj-files).</p> <p>All datasets related to this publication:</p> <p><a href="https://doi.org/10.5281/zenodo.4568113">https://doi.org/10.5281/zenodo.4568113</a>(compound <strong>1</strong>; dataset: I)</p> <p><a href="https://doi.org/10.5281/zenodo.4572444">https://doi.org/10.5281/zenodo.4572444</a> (compound <strong>1</strong>; dataset: II)</p> <p><a href="https://doi.org/10.5281/zenodo.4561797">https://doi.org/10.5281/zenodo.4561797</a>(compound <strong>2</strong>; dataset: III)</p> <p><a href="https://doi.org/10.5281/zenodo.4563896">https://doi.org/10.5281/zenodo.4563896</a> (compound <strong>2</strong>; dataset: IV)</p> <p><a href="https://doi.org/10.5281/zenodo.5563359">https://doi.org/10.5281/zenodo.5563359</a> (<strong>SB203580</strong>; dataset: V)</p> <p><a href="https://doi.org/10.5281/zenodo.5563655">https://doi.org/10.5281/zenodo.5563655</a> (<strong>SB203580</strong>; dataset: VI)</p> <p><a href="https://doi.org/10.5281/zenodo.5564118%20">https://doi.org/10.5281/zenodo.5564118 </a>(compound <strong>1</strong> simulated in compound <strong>2</strong> metastable state <strong>2-<em>S</em><sub>3</sub></strong>; dataset: VII)</p> <p><a href="https://doi.org/10.5281/zenodo.5564208%20">https://doi.org/10.5281/zenodo.5564208 </a>(compound <strong>1</strong> simulated in compound <strong>2</strong> metastable state <strong>2-<em>S</em><sub>3</sub></strong>; dataset: VIII)</p> <p><a href="https://doi.org/10.5281/zenodo.5564586">https://doi.org/10.5281/zenodo.5564586</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: IX)</p> <p><a href="https://doi.org/10.5281/zenodo.5570882">https://doi.org/10.5281/zenodo.5570882</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: X)</p> <p><a href="https://doi.org/10.5281/zenodo.5571352">https://doi.org/10.5281/zenodo.5571352</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: XI)</p> <p>The datasets include original Desmond raw-trajectories (datasets I–VIII), PDB-coordinates for the energy minimized metastable state derived structures (datasets II, IV and VI) and raw-trajectories of the well-tempered metadynamics simulations (dataset IX–XI).</p>
Protein kinase inhibitors
<p>The deposition contains data sets of human and mouse protein kinase inhibitors with reliable activity measurements and corresponding compounds classified as inactive that were assembled from public repositories. The human protein kinase inhibitors have recently been analyzed in detail [Xerxa et al., Data-Driven Global Assessment of Protein Kinase Inhibitors with Emphasis on Covalent Compounds. <em>J Med Chem</em>, 2023, in press, <a href="https://doi.org/10.1021/acs.jmedchem.3c00621">https://doi.org/10.1021/acs.jmedchem.3c00621</a>].</p>
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.