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1,487
datasets available to search
ShareScore release 0.9.0
Dataset results
1,487 results for “Tagging”
H3K36 methylation maintains cell identity by regulating opposing lineage programs [CUT&Tag]
GEO Series GSE203491. Mus musculus. 54 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Feed-forward regulatory loops by NR5A2 ensure robust gene activation during pre-implantation development [CUT&Tag, CUT&RUN, TIP-seq]
GEO Series GSE289568. Mus musculus. 43 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Other.
Age and cell type specific specific effects of histone variant H2BE in the brain [Cut&Tag]
GEO Series GSE282519. Mus musculus. 6 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
A tagged histone variant exploits cancer-specific pathway in human cells
GEO Series GSE209933. Homo sapiens. 41 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Chinmo maintains adult stem cell sex identity by directly regulating Doublesex and Insulin signaling [CUT&Tag]
GEO Series GSE201579. Drosophila melanogaster. 8 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Oncohistone H3.3K27M-driven CREB5/ID1 Axis Mediates the Malignant Cell States of Diffuse Intrinsic Pontine Glioma (DIPG) [CUT&Tag]
GEO Series GSE250464. Homo sapiens. 26 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Expression data from HEK293 Flp-In cells constitutivly expressing FLAG-HA-tagged TRIM71 and that of the parental cell line
GEO Series GSE37713. Homo sapiens. 6 samples. Type: Expression profiling by array.
Nucleus-localized S100A9 triggers senescence of human amnion fibroblasts as a heterochromatin buster at parturition - CUT&Tag
GEO Series GSE287835. Homo sapiens. 2 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
GeoVectors-Central-America-tags (v1.0)
<p><strong>Description</strong></p> <p>The GeoVectors corpus is a comprehensive large-scale linked open corpus of OpenStreetMap (https://www.openstreetmap.org/) entity embeddings that provides latent representations of over 980 million entities. The GeoVectors capture the semantic and geographic similarities of OpenStreetMap entities and make them directly accessible to machine learning applications. The "-tags" datasets provide embeddings that capture the semantic similarities of OpenStreetMap entities. The "-location" datasets provide the geographic similarities.</p> <p><strong>Contents</strong></p> <p>This dataset was derived from an OpenStreetMap snapshot that was taken on November 10, 2020 (© OpenStreetMap contributors).</p> <p>We provide the GeoVectors in region-specific subsets. This subset contains tag-embeddings for the region "Central-America" including the following countries:</p> <ul> <li>Bahamas</li> <li>Belize</li> <li>Cuba</li> <li>Guatemala</li> <li>Haiti-and-Domrep</li> <li>Jamaica</li> <li>Nicaragua</li> </ul> <p><strong>File format</strong></p> <p>The embeddings are provided in the tab-separated values (tsv) format. Each row contains the embedding of a single OpenStreetMap entity. The first column contains the OpenStreetMap type and the second column contains the OpenStreetMap id of the respective entity. The type can either be node (n), way (w), or relation (r). The remaining columns represent the dimensions of the embedding space. (See also header.tsv)</p> <p><strong>Further information:</strong></p> <p>For further information, please visit <a href="http://geovectors.l3s.uni-hannover.de">http://geovectors.l3s.uni-hannover.de</a></p> <p><strong>Funding</strong>:</p> <p>This work was partially funded by DFG, German Research Foundation (“WorldKG", DE 2299/2-1), the Federal Ministry of Education and Research (BMBF), Germany (“Simple-ML", 01IS18054), the Federal Ministry for Economic Affairs and Energy (BMWi), Germany (“d-E-mand", 01ME19009B), and the European Commission (EU H2020, “smashHit", grant-ID 871477).</p>
GeoVectors-Russia-tags (v1.0)
<p><strong>Description</strong></p> <p>The GeoVectors corpus is a comprehensive large-scale linked open corpus of OpenStreetMap (https://www.openstreetmap.org/) entity embeddings that provides latent representations of over 980 million entities. The GeoVectors capture the semantic and geographic similarities of OpenStreetMap entities and make them directly accessible to machine learning applications. The "-tags" datasets provide embeddings that capture the semantic similarities of OpenStreetMap entities. The "-location" datasets provide the geographic similarities.</p> <p><strong>Contents</strong></p> <p>This dataset was derived from an OpenStreetMap snapshot that was taken on November 10, 2020 (© OpenStreetMap contributors).</p> <p>We provide the GeoVectors in region-specific subsets. This subset contains tag-embeddings for the region "Russia" including the following countries:</p> <ul> <li>Russia</li> </ul> <p><strong>File format</strong></p> <p>The embeddings are provided in the tab-separated values (tsv) format. Each row contains the embedding of a single OpenStreetMap entity. The first column contains the OpenStreetMap type and the second column contains the OpenStreetMap id of the respective entity. The type can either be node (n), way (w), or relation (r). The remaining columns represent the dimensions of the embedding space. (See also header.tsv)</p> <p><strong>Further information:</strong></p> <p>For further information, please visit <a href="http://geovectors.l3s.uni-hannover.de">http://geovectors.l3s.uni-hannover.de</a></p> <p><strong>Funding</strong>:</p> <p>This work was partially funded by DFG, German Research Foundation (“WorldKG", DE 2299/2-1), the Federal Ministry of Education and Research (BMBF), Germany (“Simple-ML", 01IS18054), the Federal Ministry for Economic Affairs and Energy (BMWi), Germany (“d-E-mand", 01ME19009B), and the European Commission (EU H2020, “smashHit", grant-ID 871477).</p>
GeoVectors-US-South-tags (v1.0)
<p><strong>Description</strong></p> <p>The GeoVectors corpus is a comprehensive large-scale linked open corpus of OpenStreetMap (https://www.openstreetmap.org/) entity embeddings that provides latent representations of over 980 million entities. The GeoVectors capture the semantic and geographic similarities of OpenStreetMap entities and make them directly accessible to machine learning applications. The "-tags" datasets provide embeddings that capture the semantic similarities of OpenStreetMap entities. The "-location" datasets provide the geographic similarities.</p> <p><strong>Contents</strong></p> <p>This dataset was derived from an OpenStreetMap snapshot that was taken on November 10, 2020 (© OpenStreetMap contributors).</p> <p>We provide the GeoVectors in region-specific subsets. This subset contains tag-embeddings for the region "US-South" including the following countries:</p> <ul> <li>US-South</li> </ul> <p><strong>File format</strong></p> <p>The embeddings are provided in the tab-separated values (tsv) format. Each row contains the embedding of a single OpenStreetMap entity. The first column contains the OpenStreetMap type and the second column contains the OpenStreetMap id of the respective entity. The type can either be node (n), way (w), or relation (r). The remaining columns represent the dimensions of the embedding space. (See also header.tsv)</p> <p><strong>Further information:</strong></p> <p>For further information, please visit <a href="http://geovectors.l3s.uni-hannover.de">http://geovectors.l3s.uni-hannover.de</a></p> <p><strong>Funding</strong>:</p> <p>This work was partially funded by DFG, German Research Foundation (“WorldKG", DE 2299/2-1), the Federal Ministry of Education and Research (BMBF), Germany (“Simple-ML", 01IS18054), the Federal Ministry for Economic Affairs and Energy (BMWi), Germany (“d-E-mand", 01ME19009B), and the European Commission (EU H2020, “smashHit", grant-ID 871477).</p>
Am Tag der Einheit
<u>Source</u>: Flickr <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1653147473.5038.jpg">https://4dcity.org/imgupload/1653147473.5038.jpg</a> <br><u>Original Image URL</u>: <a href="https://live.staticflickr.com/65535/51089409906_c20a1a3444_m.jpg">https://live.staticflickr.com/65535/51089409906_c20a1a3444_m.jpg</a> <br><br><u>Image-Metadata:</u><br>Filename: 1653147473.5038.jpg<br>Image Dimensions: 240x176<br>Megapixels: 0.04 MP<br>Filesize: 24.18 KB<br><br>Copyright: Michael Beitelsmann<br>Artist: Michael Beitelsmann
Badsanierung - Tag 4
<u>Source</u>: Flickr <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1665391632.1391.jpg">https://4dcity.org/imgupload/1665391632.1391.jpg</a> <br><u>Original Image URL</u>: <a href="https://live.staticflickr.com/65535/52151154993_8ccd2ac860_m.jpg">https://live.staticflickr.com/65535/52151154993_8ccd2ac860_m.jpg</a> <br><br><u>Image-Metadata:</u><br>Filename: 1665391632.1391.jpg<br>Image Dimensions: 180x240<br>Megapixels: 0.04 MP<br>Filesize: 14.77 KB<br><br>ExifOffset: 38
Heute ist internationaler Tag des Kaffees
<u>Source</u>: Flickr <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1665391622.2792.jpg">https://4dcity.org/imgupload/1665391622.2792.jpg</a> <br><u>Original Image URL</u>: <a href="https://live.staticflickr.com/65535/52395837942_e27ef1ea1d_m.jpg">https://live.staticflickr.com/65535/52395837942_e27ef1ea1d_m.jpg</a> <br><br><u>Image-Metadata:</u><br>Filename: 1665391622.2792.jpg<br>Image Dimensions: 240x240<br>Megapixels: 0.06 MP<br>Filesize: 28.41 KB<br><br>ExifOffset: 38
Handeis-Adventskalender Tag 12
<u>Source</u>: Flickr <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1665256087.6009.jpg">https://4dcity.org/imgupload/1665256087.6009.jpg</a> <br><u>Original Image URL</u>: <a href="https://live.staticflickr.com/65535/51741397728_08589f020d_m.jpg">https://live.staticflickr.com/65535/51741397728_08589f020d_m.jpg</a> <br><br><u>Image-Metadata:</u><br>Filename: 1665256087.6009.jpg<br>Image Dimensions: 240x240<br>Megapixels: 0.06 MP<br>Filesize: 28.07 KB<br><br>ExifOffset: 38
Handeis-Adventskalender Tag 10
<u>Source</u>: Flickr <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1665256088.6515.jpg">https://4dcity.org/imgupload/1665256088.6515.jpg</a> <br><u>Original Image URL</u>: <a href="https://live.staticflickr.com/65535/51737693796_da2409a2f9_m.jpg">https://live.staticflickr.com/65535/51737693796_da2409a2f9_m.jpg</a> <br><br><u>Image-Metadata:</u><br>Filename: 1665256088.6515.jpg<br>Image Dimensions: 240x240<br>Megapixels: 0.06 MP<br>Filesize: 30.11 KB<br><br>ExifOffset: 38
Handeis-Adventskalender Tag 22
<u>Source</u>: Flickr <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1665256083.6608.jpg">https://4dcity.org/imgupload/1665256083.6608.jpg</a> <br><u>Original Image URL</u>: <a href="https://live.staticflickr.com/65535/51764708942_a85139d55e_m.jpg">https://live.staticflickr.com/65535/51764708942_a85139d55e_m.jpg</a> <br><br><u>Image-Metadata:</u><br>Filename: 1665256083.6608.jpg<br>Image Dimensions: 240x240<br>Megapixels: 0.06 MP<br>Filesize: 29.57 KB<br><br>ExifOffset: 38
Handeis-Adventskalender Tag 9
<u>Source</u>: Flickr <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1665256006.1183.jpg">https://4dcity.org/imgupload/1665256006.1183.jpg</a> <br><u>Original Image URL</u>: <a href="https://live.staticflickr.com/65535/51735853858_541d3f2a39_m.jpg">https://live.staticflickr.com/65535/51735853858_541d3f2a39_m.jpg</a> <br><br><u>Image-Metadata:</u><br>Filename: 1665256006.1183.jpg<br>Image Dimensions: 240x240<br>Megapixels: 0.06 MP<br>Filesize: 30.54 KB<br><br>ExifOffset: 38
Handeis-Adventskalender Tag 14
<u>Source</u>: Flickr <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1665256003.8968.jpg">https://4dcity.org/imgupload/1665256003.8968.jpg</a> <br><u>Original Image URL</u>: <a href="https://live.staticflickr.com/65535/51746673486_3a36df92ff_m.jpg">https://live.staticflickr.com/65535/51746673486_3a36df92ff_m.jpg</a> <br><br><u>Image-Metadata:</u><br>Filename: 1665256003.8968.jpg<br>Image Dimensions: 240x240<br>Megapixels: 0.06 MP<br>Filesize: 31.16 KB<br><br>ExifOffset: 38
Handeis-Adventskalender Tag 20
<u>Source</u>: Flickr <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1665256002.0052.jpg">https://4dcity.org/imgupload/1665256002.0052.jpg</a> <br><u>Original Image URL</u>: <a href="https://live.staticflickr.com/65535/51759378198_c7eb0036a3_m.jpg">https://live.staticflickr.com/65535/51759378198_c7eb0036a3_m.jpg</a> <br><br><u>Image-Metadata:</u><br>Filename: 1665256002.0052.jpg<br>Image Dimensions: 240x240<br>Megapixels: 0.06 MP<br>Filesize: 29.36 KB<br><br>ExifOffset: 38
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.