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476 results for “footprints”

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geo20/100

Regulation of nucleosome architecture and factor binding revealed by nuclease footprinting of the ESC genome

GEO Series GSE68400. Mus musculus. 16 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Third-party reanalysis.

openGEO-OpenAug 2015View details →
geo20/100

Mutant NPM1 marginally impacts ribosome footprint in acute myeloid leukemia cells

GEO Series GSE251919. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing; Other.

openGEO-OpenSep 2024View details →
geo20/100

PGC 1α Senses the CBC of Pre-mRNA to Dictate the Fate of Promoter-Proximally Paused RNAPII [RIP-seq footprint]

GEO Series GSE197279. Mus musculus. 9 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenJan 2023View details →
geo20/100

Evidence of an Increased Pathogenic Footprint in the Lingual Microbiome of Untreated HIV Infected Patients

GEO Series GSE38908. Homo sapiens; Bacteria. 21 samples. Type: Expression profiling by array.

openGEO-OpenJun 2012View details →
geo20/100

Epigenetic footprint of hepatoblastoma defines a novel integrative molecular classification with clinical implications

GEO Series GSE132219. Homo sapiens. 206 samples. Type: Expression profiling by array; Genome variation profiling by SNP array; Methylation profiling by genome tiling array; Expression profiling by high throughput sequencing.

openGEO-OpenMar 2020View details →
geo20/100

Ribosomal footprinting of MDA_Ctrl and MDA_Glu overexpression cell lines

GEO Series GSE77347. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenJun 2016View details →
geo20/100

Identification of genes essential for Moraxella catarrhalis growth under iron-limiting conditions using Genomic Array Footprinting (GAF)

GEO Series GSE41546. Moraxella catarrhalis BBH18. 24 samples. Type: Genome variation profiling by genome tiling array; Other.

openGEO-OpenJun 2013View details →
geo20/100

LMX1B missense-perturbation of regulatory element footprints disrupt postnatal serotonergic forebrain axon arborization [ATAC-seq]

GEO Series GSE283962. Mus musculus. 8 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.

openGEO-OpenMar 2025View details →
geo20/100

SARS-CoV-2 viral RNA disseminates to hamster toes and associates with localized IFN-I production: mechanistic footprints of an abortive COVID-19 infection in pandemic-associated pernio

GEO Series GSE232226. Mesocricetus auratus; Homo sapiens. 38 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenSep 2024View details →
geo20/100

Tissue-specific transcription footprinting using RNA PolII DamID (RAPID) in C. elegans

GEO Series GSE157418. Caenorhabditis elegans. 28 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.

openGEO-OpenOct 2020View details →
geo20/100

High-resolution CTCF footprinting reveals impact of chromatin state on cohesin extrusion [RCMC]

GEO Series GSE285012. Mus musculus. 6 samples. Type: Other.

openGEO-OpenJan 2025View details →
geo20/100

Genome-wide reduction in chromatin accessibility and unique transcription factor footprints in endothelial cells and fibroblasts in scleroderma skin

GEO Series GSE163199. Homo sapiens. 24 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.

openGEO-OpenSep 2022View details →
geo20/100

Demonstration of CUT&RUN motif footprint analysis using key blood progenitor transcription factors

GEO Series GSE136251. Homo sapiens. 5 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.

openGEO-OpenAug 2019View details →
geo20/100

Cell-free DNA comprises an in vivo, genome-wide nucleosome footprint that informs its tissue(s)-of-origin

GEO Series GSE71378. Homo sapiens. 60 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.

openGEO-OpenNov 2015View details →
geo20/100

LNCap cell nucleosome footprint elicits novel noncanonical GATA2 pioneer model

GEO Series GSE148935. Homo sapiens. 44 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.

openGEO-OpenApr 2021View details →
zenodo20/100

RELATIONSHIP BETWEEN NUTRIENT PROFILES, CARBON, AND WATER FOOTPRINT OF HOSPITAL MENUS

Open the record for dataset details and reuse information.

opencc-by-4.0Nov 2023View details →
zenodo20/100

SM Footprint Study - ERL

Open the record for dataset details and reuse information.

opencc-by-4.0Dec 2023View details →
zenodo20/100

China's first sub-meter building footprints derived by deep learning (part 2 of 2).

<h1><strong>Download</strong></h1> <p>Due to Zenodo's file size limitations, we are releasing <strong>different parts</strong> of CBF and GBD in <strong>different versions</strong>. See the below for specific information:</p> <p><strong>1. China's first sub-meter building footprints (CBF) derived by deep learning:</strong></p> <ul> <li>part1: version12 (v12), City 1 to 210, <a href="https://doi.org/10.5281/zenodo.10473278">https://doi.org/10.5281/zenodo.10473278</a></li> <li>part2: version13 (v13),&nbsp;City 211 to 356,&nbsp;<a href="https://doi.org/10.5281/zenodo.10475803">https://doi.org/10.5281/zenodo.10475803 <strong>(current version)</strong></a></li> </ul> <p>&nbsp; &nbsp; &nbsp; <strong>Building attributes:</strong></p> <ul> <li>id: Index number of the current building.</li> <li>year: Year of construction retrieved from GISA.</li> <li>height_mean: The average height of the building (computed from the pixels within the building footprint) obtained from CNBH (meters).</li> <li>height_max: Maximum height of the building (based on the highest pixel value within the building footprint) obtained from CNBH (meters).</li> <li>height_min: Minimum height of the building (based on the lowest pixel value within the building footprint) obtained from CNBH (meters).</li> <li>miniDist: Shortest straight-line distance to another building.</li> <li>dist_id: Index number of the building with the shortest straight-line distance to the current building.</li> <li>area: Area of the current building (square meters).</li> <li>perimeter: Perimeter of the current building (meters).</li> <li>inurban_19: A value of 1 indicates that the building was situated in an urban area in 1990, while a value of 0 signifies that it was located in a rural area in 1990. This determination is made using GUB data.</li> <li>inurban_1: A value of 1 indicates that the building was situated in an urban area in 1995, while a value of 0 signifies that it was located in a rural area in 1995. This determination is made using GUB data.</li> <li>inurban_20: A value of 1 indicates that the building was situated in an urban area in 2000, while a value of 0 signifies that it was located in a rural area in 2000. This determination is made using GUB data.</li> <li>inurban_2: A value of 1 indicates that the building was situated in an urban area in 2005, while a value of 0 signifies that it was located in a rural area in 2005. This determination is made using GUB data.</li> <li>inurban_3: A value of 1 indicates that the building was situated in an urban area in 2010, while a value of 0 signifies that it was located in a rural area in 2010. This determination is made using GUB data.</li> <li>inurban_4: A value of 1 indicates that the building was situated in an urban area in 2015, while a value of 0 signifies that it was located in a rural area in 2015. This determination is made using GUB data.</li> <li>inurban_5: A value of 1 indicates that the building was situated in an urban area in 2020, while a value of 0 signifies that it was located in a rural area in 2020. This determination is made using GUB data.</li> </ul> <p>&nbsp;</p> <p><strong>2. Global Building Dataset (GBD):</strong></p> <p>This dataset comprises approximately 800,000 images(512*512) with diverse architectural styles worldwide. It can be served as training and test samples for building extraction in different regions globally. In order to enhance usability, we did not break the continuity of the image and published it in 1024*1024 size.</p> <table> <tbody> <tr> <td>Version</td> <td>description</td> <td>link</td> </tr> <tr> <td>v1</td> <td>All labels. Images of Africa, Australia, and South America.</td> <td><a href="../records/10043352">https://zenodo.org/records/10043352</a></td> </tr> <tr> <td>v2</td> <td>image of Asia (part 1 to 30 of 53).</td> <td><a href="../records/10456238">https://zenodo.org/records/10456238</a></td> </tr> <tr> <td>v3</td> <td>image of Asia (part 31 to 53 of 53).</td> <td><a href="../records/10457368">https://zenodo.org/records/10457368</a></td> </tr> <tr> <td>v4</td> <td>image of Europe (part 1 to 21 of 58).</td> <td><a href="../records/10458273">https://zenodo.org/records/10458273</a></td> </tr> <tr> <td>v5</td> <td>image of Europe (part 21 to 42 of 58).</td> <td><a href="../records/10460868">https://zenodo.org/records/10460868</a></td> </tr> <tr> <td>v6</td> <td>image of Europe (part 43 to 58 of 58).</td> <td><a href="../records/10462506">https://zenodo.org/records/10462506</a></td> </tr> <tr> <td>v7</td> <td>image of North America (part 1 to 20 of 93).</td> <td><a href="../records/10463385">https://zenodo.org/records/10463385</a></td> </tr> <tr> <td>v8</td> <td>image of North America (part 21 to 40 of 93).</td> <td><a href="../records/10465076">https://zenodo.org/records/10465076</a></td> </tr> <tr> <td>v9</td> <td>image of North America (part 41 to 60 of 93).</td> <td><a href="../records/10466569">https://zenodo.org/records/10466569</a></td> </tr> <tr> <td>v10</td> <td>image of North America (part 61 to 80 of 93).</td> <td><a href="../records/10467291">https://zenodo.org/records/10467291</a></td> </tr> <tr> <td>v11</td> <td>image of North America (part 81 to 93 of 93).</td> <td><a href="../records/10471557">https://zenodo.org/records/10471557</a></td> </tr> </tbody> </table> <p>&nbsp;</p>

restrictedcc-by-4.0Jan 2024View details →
zenodo20/100

Mapping roadless areas in regions with contrasting human footprint

Open the record for dataset details and reuse information.

opencc-by-4.0Feb 2024View details →
zenodo20/100

Footprints - Rhynchosaur

# SHCMS:G.12872 **Rhynchosaur footprints** Fine-grained sandstone slab preserving the footprints of a Triassic rhynchosaur. Found at Grinshill, Shropshire. Age: approx 225 million years. Length 25cm Width 12.5cm Depth 1.5cm. Imaged using an Artec spider scanner and processed using Artec studio 12. If you like this model or any others we produce we'd love to hear from you and how you've used them. Source: Objaverse 1.0 / Sketchfab

opencc-by-nc-1.0Mar 2019View details →

ScienceDex guides

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record