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1,063 results for “Search”

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nasa20/100

Kepler Target Search

The Kepler Target Search interface provides access to a 12.5 million row table created by MAST by joining entries from the Kepler Input catalog (KIC) with the Kepler Characteristics table (CT) and merging these with "associated" entries from the United Kingdom Infrared Telescope (IRT) project, the USNOb catalog, GALEX, the Kepler Isaac Newton Telescope Survey (KIS), and the Everett KPNO (UBV) survey. The search interface allows users to find targets within the Kepler field of view (FOV) and allows searches on magnitudes, colors, and other parameters for both KIC and associated non-KIC targets.This is the recommended interface for potential guest observers to locate possible targets for observation. GO proposers however should check on the target's position by either (or both) looking to one of our posted FFI images and seeing if it is on a chip, and (2) confirming this with the GO office.

restrictednotspecifiedApr 2025View details →
nasa20/100

MMS 3 Search Coil Magnetometer (SCM) AC Magnetic Field Level 2 (L2), High Speed Burst Mode, 16384 Sample/s Data

Search Coil Magnetometer (SCM) AC Magnetic Field (16384 samples/s), Level 2, High Speed Burst Mode Data. The tri-axial Search-Coil Magnetometer with its associated preamplifier measures three-dimensional magnetic field fluctuations. The analog magnetic waveforms measured by the SCM are digitized and processed inside the Digital Signal Processor (DSP), collected and stored by the Central Instrument Data Processor (CIDP) via the Fields Central Electronics Box (CEB). Prior to launch, all SCM Flight models were calibrated by LPP team members at the National Magnetic Observatory, Chambon-la-Foret (Orleans). Once per orbit, each SCM transfer function is checked thanks to the onboard calibration signal provided by the DSP. The SCM is operated for the entire MMS orbit in survey mode. Within scientific Regions Of Interest (ROI), burst mode data are also acquired as well as high speed burst mode data. This SCM data set corresponds to the AC magnetic field waveforms in nanoTesla and in the GSE frame. The SCM instrument paper for SCM can be found at http://link.springer.com/article/10.1007/s11214-014-0096-9 and the SCM data product guide at https://lasp.colorado.edu/mms/sdc/public/datasets/fields/.

restrictednotspecifiedAug 2025View details →
nasa20/100

MMS 1 Search Coil Magnetometer (SCM) AC Magnetic Field Level 2 (L2), Burst Mode, 8192 Sample/s Data

Search Coil Magnetometer (SCM) AC Magnetic Field (8192 samples/s), Level 2, Burst Mode Data. The tri-axial Search-Coil Magnetometer with its associated preamplifier measures three-dimensional magnetic field fluctuations. The analog magnetic waveforms measured by the SCM are digitized and processed inside the Digital Signal Processor (DSP), collected and stored by the Central Instrument Data Processor (CIDP) via the Fields Central Electronics Box (CEB). Prior to launch, all SCM Flight models were calibrated by LPP team members at the National Magnetic Observatory, Chambon-la-Foret (Orleans). Once per orbit, each SCM transfer function is checked thanks to the onboard calibration signal provided by the DSP. The SCM is operated for the entire MMS orbit in survey mode. Within scientific Regions Of Interest (ROI), burst mode data are also acquired as well as high speed burst mode data. This SCM data set corresponds to the AC magnetic field waveforms in nanoTesla and in the GSE frame. The SCM instrument paper for SCM can be found at http://link.springer.com/article/10.1007/s11214-014-0096-9 and the SCM data product guide at https://lasp.colorado.edu/mms/sdc/public/datasets/fields/.

restrictednotspecifiedAug 2025View details →
geo16/100

The search of genetic resources for parthenocarpic pears and comparison of gene expression between high and low parthenocarpy cultivars

GEO Series GSE27090. Pyrus hybrid cultivar; Pyrus pyrifolia; Pyrus communis; Pyrus communis x Pyrus pyrifolia. 12 samples. Type: Expression profiling by array.

openGEO-OpenJan 2012View details →
geo16/100

The use of zebrafish reward mutants to search for novel transcripts mediating the behavioral effects of amphetamine

GEO Series GSE14399. Danio rerio. 3 samples. Type: Expression profiling by array.

openGEO-OpenJan 2009View details →
geo16/100

Cohesin regulates homology search during recombinational DNA repair

GEO Series GSE179646. Saccharomyces cerevisiae W303. 101 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.

openGEO-OpenJul 2021View details →
geo16/100

Search for biomarkers of response to MitoQ in human breast cancer cell lines

GEO Series GSE148111. Homo sapiens. 16 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenSep 2021View details →
geo16/100

Mesoscale chromatin confinement facilitates target search of pioneer transcription factors in live cells

GEO Series GSE203650. Homo sapiens. 40 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.

openGEO-OpenApr 2024View details →
geo16/100

Searching for the mechanism that mediates mefenoxam-acquired resistance in Phytophthora infestans and how it is regulated

GEO Series GSE186905. Phytophthora infestans. 18 samples. Type: Non-coding RNA profiling by high throughput sequencing.

openGEO-OpenDec 2021View details →
geo16/100

Optimal settings of mass spectrometry open search strategy for higher confidence

GEO Series GSE112623. Homo sapiens. 3 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenOct 2018View details →
geo16/100

Studying heterogeneity in embryonic stem cells using the approach of search-engine

GEO Series GSE192644. Mus musculus. 190 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.

openGEO-OpenDec 2022View details →
geo16/100

Searching genes responsible for developmental origins of health and disease (DOHaD) by comparing adult and fetal mouse undernutrition models

GEO Series GSE78817. Mus musculus. 6 samples. Type: Expression profiling by array.

openGEO-OpenMar 2016View details →
geo16/100

Search for a novel therapeutic target in myeloid leukemia

GEO Series GSE79605. Homo sapiens. 4 samples. Type: Expression profiling by array.

openGEO-OpenMay 2016View details →
geo16/100

Search for apoptosis-related transcriptome markers associated with herpesvirus infections in peripheral blood leukocytes

GEO Series GSE109961. Homo sapiens. 193 samples. Type: Expression profiling by array.

openGEO-OpenJan 2018View details →
geo16/100

PGS: penalized generalized estimating equations with grid search for epigenome-wide multiple measurement study

GEO Series GSE55950. Homo sapiens. 228 samples. Type: Non-coding RNA profiling by array.

openGEO-OpenDec 2017View details →
geo16/100

Mesoscale chromatin confinement facilitates target search of pioneer transcription factors in live cells [ChIP-seq]

GEO Series GSE203644. Homo sapiens. 17 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.

openGEO-OpenApr 2024View details →
geo16/100

Mesoscale chromatin confinement facilitates target search of pioneer transcription factors in live cells [RNA-seq]

GEO Series GSE203640. Homo sapiens. 11 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenApr 2024View details →
geo16/100

Transcriptome analysis of chemically polarised rat macrophages: in search of target genes for ARDS therapy

GEO Series GSE266262. Rattus norvegicus. 9 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenApr 2025View details →
zenodo16/100

Mediation of Presence and Search for Meaning in Life between Spiritual Experience and Personal Growth of the Filipino Emerging Adults

<p>Data Set</p>

restrictedcc-by-4.0Nov 2023View details →
zenodo16/100

Data set of "Context-sensitive Requirements Search in Natural Language Specifications"

<p>We use this data set for the evaluation of our Context-sensitive Requirements Search approach. It contains three files and 15 searches.</p> <p>&nbsp;</p> <p><strong>Attribution</strong></p> <p>The foundation of this data set is PURE:<br> A. Ferrari, G. O. Spagnolo, and S. Gnesi. <em>PURE: a Dataset of Public Requirements Documents</em>. Version 1.0. Sept. 2018.<br> Available at:&nbsp;<a href="https://doi.org/10.5281/zenodo.1414117">https://doi.org/10.5281/zenodo.1414117</a></p> <p>The original data is licensed under <a href="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</a></p> <p>&nbsp;</p> <p><strong>Annotations</strong></p> <ul> <li>Each of the provided files contains annotations that we created with Label Studio for the corresponding file of the PURE data set.</li> <li>These annotations depict the search results of Plain Keyword Search (PKS) and the corresponding gold standard.</li> <li>The following is an example of an annotation in the .json file:</li> </ul> <pre><code class="language-json">{ "id": "UnaxUjB6oY", "meta": { "text": ["0"] }, "type": "labels", "value": { "end": "/text()[2]", "text": "speed", "start": "/text()[2]", "labels": ["speed: train speed profile"], "endOffset": 364, "startOffset": 359, "globalOffsets": { "end": 1403, "start": 1398 } }, "origin": "manual", "to_name": "text", "from_name": "ner" },</code></pre> <p>&nbsp;</p> <p><strong>Important Json attributes to consider</strong></p> <p><strong>Meta</strong></p> <p>We encode the relevance of each result in its metadata.</p> <p><em>Example:</em></p> <pre><code class="language-json">"meta": { "text": ["0"] },</code></pre> <ul> <li>1 = relevant for this search and found by PKS</li> <li>0 = irrelevant for this search but found by PKS</li> <li>-1 = relevant for this search and not found by PKS</li> </ul> <p>&nbsp;</p> <p><strong>Labels</strong></p> <p>This element is the search identifier we use in Label Studio. It corresponds to the table in the thesis that describes each search in detail.</p> <p><em>Example:</em></p> <pre><code class="language-json">"labels": ["speed: train speed profile"],</code></pre> <p>&nbsp;</p> <p><strong>GlobalOffsets</strong></p> <p>&quot;globalOffsets&quot; describes the position of a label in the text.</p> <p><em>Example:</em></p> <pre><code class="language-json">"globalOffsets": { "end": 1403, "start": 1398 }</code></pre> <p>&nbsp;</p>

restrictedMar 2022View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

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

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Your academic CV and NIH biosketch

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