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123
datasets available to search
ShareScore release 0.9.0
Dataset results
123 results for “Target detection”
Detection RNA targets interacting with RBM8A in AGS cells
GEO Series GSE292233. Homo sapiens. 6 samples. Type: Other.
Clinical Utility of Targeted Next-Generation Sequencing Assay to Detect Copy Number Variants in Myeloid Malignancies: Is It Ready for Prime Time?
GEO Series GSE165733. Homo sapiens. 91 samples. Type: Genome variation profiling by high throughput sequencing.
Targeted bisulfite sequencing to detect TALE-DNMT mediated targeted DNA methylation in human cells
GEO Series GSE66456. Homo sapiens. 42 samples. Type: Methylation profiling by high throughput sequencing.
DNA copy number detection from exome sequencing - Exploiting the off-targets
GEO Series GSE60259. Homo sapiens; Mus musculus. 10 samples. Type: Genome variation profiling by genome tiling array; Genome variation profiling by SNP array.
Detect-seq on transfected HEK293T cells [Targeted deep sequencing data]
GEO Series GSE176089. Homo sapiens. 1350 samples. Type: Other.
The mitochondrial-targeted peptide therapeutic elamipretide improves cardiac and skeletal muscle function during aging without detectable changes in tissue epigenetic or transcriptomic age.
GEO Series GSE280700. Macaca mulatta; Homo sapiens; Rattus; Mus musculus. 114 samples. Type: Expression profiling by high throughput sequencing; Methylation profiling by genome tiling array.
Detection of Notch1-IC, Notch2-IC and EBNA2 target genes in human B cells
GEO Series GSE12355. Homo sapiens. 41 samples. Type: Expression profiling by array.
DNA copy number detection from exome sequencing - Exploiting the off-targets (Nimblegen)
GEO Series GSE60254. Mus musculus. 4 samples. Type: Genome variation profiling by genome tiling array.
CoRoT Stellar Targets for Exoplanet Detection Observation Log
CoRoT was a space astronomy mission devoted to the study of the variability with time of stars' brightness, with an extremely high accuracy (100 times better than from the ground), for very long durations (up to 150 days) and with a very high duty cycle (more than 90%). The mission was led by CNES in association with four French laboratories, and 7 participating countries and agencies (Austria, Belgium, Brazil, Germany, Spain, and the ESA Science Programme). The satellite is composed of a PROTEUS platform (the 3rd in the series), and a unique instrument: a stellar photometer. It was launched on December 27th, 2006 on a Soyuz Rocket, from Baikonour. The mission has lasted almost 6 years (the nominal 3 years duration and a 3 years extension) and has observed more than 160,000 stars. It suddenly stopped sending data on November 2nd, 2012. CoRoT performed Ultra High Precision Photometry of Stars to detect and characterize the variability of their luminosity with two main objectives: (i) the variability of the object itself: oscillations, rotation, magnetic activity, etc.; (ii) variability due to external causes such as bodies in orbit around the star: planets and companion stars. The original scientific objectives were focused on the study of stellar pulsations (asteroseismology) to probe the internal structure of stars, and the detection of small exoplanets through their transit in front of their host star, and the measurement of their sizes. This lead to the introduction of two modes of observations, working simultaneously: - The bright star mode dedicated to very precise seismology of a small sample (171) of bright and nearby stars (presented in the file named "Bright_star.dat" in the CDS version at <a href="https://cdsarc.cds.unistra.fr/ftp/cats/B/corot/">https://cdsarc.cds.unistra.fr/ftp/cats/B/corot/</a>): these data are not included in this HEASARC table, notice; - The faint star mode, observing a very large number of stars at the same time, to detect transits, which are rare events, as they imply the alignment of the star, the planet and the observer (these data are presented in the file named "Faint_star.dat" in the CDS version at <a href="https://cdsarc.cds.unistra.fr/ftp/cats/B/corot/">https://cdsarc.cds.unistra.fr/ftp/cats/B/corot/</a>): this HEASARC table is based on this sample. The large amount of data gathered in this mode mode turned out to be extremely fruitful for many topics of stellar physics. Due to project constraints, two regions of the sky were accessible (circles of 10 degrees centered on the equator around Right Ascensions of 06<sup>h</sup> 50<sup>m</sup> and 18<sup>h</sup> 50<sup>m</sup>). They are called the CoRoT 'eyes': the first one is called the "anticenter" eye, whereas the second one is called the "center eye". Each pointing covers 1.4 x 2.8 square degrees. The CoRoT project is still processing the data, aiming at removing instrumental artifacts and defects. Therefore the format and content of the catalog is still somewhat evolving. More details on the data can be found in the file <a href="http://idoc-corotn2-public.ias.u-psud.fr/jsp/doc/CoRoT_N2_versions_30sept2014.pdf">http://idoc-corotn2-public.ias.u-psud.fr/jsp/doc/CoRoT_N2_versions_30sept2014.pdf</a>. More details on the CoRoT N2 data may be found in the documentation file <a href="http://idoc-corotn2-public.ias.u-psud.fr/jsp/doc/DescriptionN2v1.5.pdf">http://idoc-corotn2-public.ias.u-psud.fr/jsp/doc/DescriptionN2v1.5.pdf</a>. This HEASARC table contains information on stars observed by CoRoT in its exoplanet detection program. A few percent of these stars have 2 entries since they were observed in different windows (as specified by the corot_window_id parameter) in a subsequent observing run to the initial run in which they were observed. Each entry in this table corresponds to the unique specification of target and corot_window_id, each with a link to its associated N2 data products. The original names of the parameters in this table, as given in the CoRoT mission documentation, are given in square brackets at the end of the parameter descriptions listed below. This table was created by the HEASARC in May 2012 based on <a href="https://cdsarc.cds.unistra.fr/ftp/cats/B/corot">CDS Catalog B/corot</a> file Faint_star.dat. The HEASARC routinely updates this table after updates are made to the CDS version of this catalog. This is a service provided by NASA HEASARC .
From mouse to humans: detecting preventing vaccination targets associated to melanoma cancer stem cells. Gene-level analysis: CT26
GEO Series GSE60647. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
From mouse to humans: detecting preventing vaccination targets associated to melanoma cancer stem cells. Gene-level analysis: B16
GEO Series GSE60556. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
Genome-wide Detection of Genes Targeted by Aberrant Somatic Hypermutation in Lymphoma
GEO Series GSE34316. Homo sapiens. 4 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
From mouse to humans: detecting preventing vaccination targets associated to melanoma cancer stem cells. Gene-level analysis: TUBO
GEO Series GSE60648. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
From mouse to humans: detecting preventing vaccination targets associated to breast cancer stem cells. Gene-level analysis
GEO Series GSE21451. Mus musculus. 12 samples. Type: Expression profiling by array.
Transient in vivo base editing with no detectable RNA- and DNA off-target mutations
GEO Series GSE148349. Homo sapiens; Mus musculus. 66 samples. Type: Expression profiling by high throughput sequencing.
From mouse to humans: detecting preventing vaccination targets associated to breast cancer stem cells
GEO Series GSE21486. Mus musculus. 31 samples. Type: Expression profiling by array.
Detection and Targeting of Splicing Deregulation in Pediatric Acute Myeloid Leukemia Stem Cells
This study evaluates the gene expression and splicing changes between pediatric patients with and without Acute Myeloid Leukemia (AML) and pediatric and adult patients with AML. We obtained bone marrow or peripheral blood from patients and isolated CD34+ stem and/or progenitor cells from pediatric patients with AML (10) or without AML (6) and adult patients with AML (5). In parallel, a targeted analysis for known, deleterious, genetic mutations in the KRAS, NRAS, and KMT2C genes identified 2, 5, and 6 AML patients with alterations, respectively. Additionally, Tapestri analysis further identified a mutation in the intronic region of the SF3B1 gene in multiple pediatric AML patients. RNA-Seq was performed on the purified cell populations at The Scripps Research Institute Next Generation Core on an Illumina NextSeq 500 sequencer with 150bp paired-end reads. These datasets revealed that, similar to adult AML, pediatric AML samples were enriched for Leukemia Stem Cells (LSC) markers. A deeper analysis showed widespread dysregulation of splicing in pediatric AML samples compared to age-matched non-leukemic samples. In addition, the splicing regulator RBFOX2 was downregulated with an accompanying increase in specific CD47 splice isoforms in the pediatric AML samples. Thus, the increased presence of LSCs in pediatric AML is possibly driven by global splicing deregulation, and the treatment with splicing modulators like Rebecsinib has a potential therapeutic value for eradicating LSCs in these patients.
Dataset for: "Disturbed YouTube for Kids: Characterizing and Detecting Inappropriate Videos Targeting Young Children"
<p>Dataset for paper: Disturbed YouTube for Kids: Characterizing and Detecting Inappropriate Videos Targeting Young Children</p> <p>The dataset consists of five files:<br> 1. groundtruth_videos.json: This is the ground truth dataset. We have 4797 manually annotated videos (1513 suitable, 929 disturbing, 419 restricted, and 1936 irrelevant). You can distinguish among the different labels by observing the 'classification_label' field.<br> 2. elsagate_related_videos.json: Contains the data for 233K elsagate-related YouTube videos (1K seed and 232K recommended) that were obtained as described in the paper.<br> 3. other_child_related_videos.json: Contains the data for 155K other child-related YouTube videos (2K seed and 153K recommended) that were obtained as described in the paper.<br> 4. random_videos.json: Contains the data for 482K random YouTube videos (8K seed and 474K recommended) that were obtained as described in the paper.<br> 5. popular_videos.json: Contains the data for 11K popular YouTube videos (500 seed and 10.5K recommended) that were obtained between November 18 and November 21, 2018, as described in the paper.</p> <p>For each video in all sets, you can check the predicted label of our classifier by observing the 'prediction' field.</p>
From mouse to humans: detecting preventing vaccination targets associated to breast cancer stem cells. Exon-level analysis
GEO Series GSE21475. Mus musculus. 19 samples. Type: Expression profiling by array.
Evaluation of Target Preparation Methods for Single-Feature Polymorphism Detection in Large Complex Plant Genomes
GEO Series GSE12770. Zea mays. 36 samples. Type: Other.
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.