Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
49
datasets available to search
ShareScore release 0.9.0
Dataset results
49 results for “Structure probing”
FragSeq: transcriptome-wide RNA structure probing using high-throughput sequencing.
GEO Series GSE24622. Mus musculus. 10 samples. Type: Other.
DMS-MaPseq: A genome-wide or targeted approach for RNA structure probing in vivo
GEO Series GSE84537. Saccharomyces cerevisiae; Homo sapiens; Drosophila melanogaster. 29 samples. Type: Expression profiling by high throughput sequencing.
smartSHAPE: a low-input method for transcriptome-wide RNA structure probing uncovers RNA structure landscape in mouse colonic macrophages
GEO Series GSE155961. Homo sapiens; Mus musculus. 36 samples. Type: Expression profiling by high throughput sequencing; Other.
Nano-structural analysis of engrafted human induced pluripotent stem cell-derived cardiomyocytes in mouse hearts using a genetic-probe APEX2.
GEO Series GSE99470. Homo sapiens. 32 samples. Type: Expression profiling by array.
Genome-wide probing of RNA structure reveals active unfolding of mRNA structures in vivo
GEO Series GSE45803. Homo sapiens; Saccharomyces cerevisiae. 25 samples. Type: Other.
Carbodiimide reagents for the chemical probing of RNA structure in cells
GEO Series GSE118309. Homo sapiens; Mus musculus. 42 samples. Type: Other.
Probing in vivo RNA structure with optimized DMS-MaPseq in rice
GEO Series GSE197245. Oryza sativa; Arabidopsis thaliana; Oryza sativa Japonica Group. 17 samples. Type: Other; Expression profiling by high throughput sequencing.
Structure-seq2 probing of RNA structure upon amino acid starvation reveals both known and novel RNA switches in Bacillus subtilis
GEO Series GSE148936. Bacillus subtilis. 14 samples. Type: Expression profiling by high throughput sequencing; Other.
A new reagent for in vivo structure probing of RNA G and U residues that improves RNA structure prediction alone and combined with DMS
GEO Series GSE254895. Escherichia coli. 33 samples. Type: Other.
Transcriptome-Wide Combinatorial RNA Structure Probing in Living Cells with icSHAPE and icLASER
GEO Series GSE132099. Homo sapiens. 14 samples. Type: Expression profiling by high throughput sequencing; Other.
In vivo structure probing of RNA in Archaea: Novel insights into the ribosome structure of Methanosarcina acetivorans
GEO Series GSE229536. Methanosarcina acetivorans C2A. 12 samples. Type: Other.
On Open and Strong-Scaling Tools for Atom Probe Crystallography: High-Throughput Methods for Indexing Crystal Structure and Orientation
<p>This repository contains XML configuration files, POS and EPOS reconstructed APT datasets and RNG/RRNG range files, raw data, and synthetic dataset to follow our analysis made in the initial version of the paper <em>"On Open and Strong-Scaling Tools for Atom Probe Crystallography: High-Throughput Methods for Indexing Crystal Structure and Orientation"</em></p> <p>We are continuously working on the atom probe crystallography tools of paraprobe and their corresponding configuration and analysis wizards in paraprobe-parmsetup and paraprobe-autoreporter. Also, we are currently working on an ontology for metadata of APT post-processing workflows. Therefore, changes in the structure of the HDF5 file are expected to come up.<br> <br> Therefore, we always recommend to work with the newest code of PARAPROBE on the GitLab:</p> <p><strong>https://gitlab.mpcdf.mpg.de/mpie-aptfim-toolbox/paraprobe.git<br> https://paraprobe-toolbox.readthedocs.io/en/latest/</strong></p> <p>Therefore, the data in here serve as a reference to and documentation of the settings mainly.</p> <p><strong>This repository here contains the following pieces of information:</strong></p> <p><strong>VerifyCrystalStructures_Geo26Al.zip<br> VerifyCrystalStructures_Geo26Al3Sc.zip<br> VerifyCrystalStructures_Geo26W.zip</strong><br> Raw data and results for the assessment of the histograms and SDMs and corresponding amplitude spectra.</p> <p><strong>VerifySXIndexing.zip</strong><br> Raw data and results for the verification with synthetic single crystal datasets.</p> <p><strong>VerifyPXIndexing2_SimID.200.tar.gz<br> VerifyPXIndexing2_SimID.201.tar.gz<br> VerifyPXIndexing2_SimID.202.tar.gz</strong><br> Raw data and results for the verification with synthetic polycrystal datasets,<br> where 200 is without noise, 201 low noise, 202 high noise.</p> <p><strong>VerifyAlBicrystalZirong_ExampleROIs.tar.gz<br> VerifyAlBicrystalZirong_Library.tar.gz</strong><br> <strong>VerifyAlBicrystalZirong_Setup.tar.gz<br> VerifyAlBicrystalZirongRendering.zip</strong><br> Raw data and results for specific ROIs discussed for the aluminium bicrystal including Paraview example for rendering.</p> <p><strong>VerifyAlLiMgBaptiste_ExampleROIs.tar.gz<br> VerifyAlLiMgBaptiste_Library.tar.gz<br> VerifyAlLiMgBaptiste_Setup.tar.gz<br> VerifyAlLiMgBaptisteRendering.zip</strong><br> Raw data and results for specific ROIs discussed for the aluminium bicrystal including Paraview example for rendering.</p> <p><strong>AlBicrystalAdaptiveROIGrid.tar.gz<br> AlLiMgAgAdaptiveROIGrid.tar.gz</strong><br> Raw data and results for the tutorial with adaptive refinement of the ROI grid, as it is detailed in the Jupyter notebook tutorials on the GitLab repository.</p> <p> </p>
A small cationic probe highly selective for RNA tertiary structure
GEO Series GSE286293. Escherichia coli; Geobacillus stearothermophilus; Oceanobacillus iheyensis; Orthoflavivirus denguei. 41 samples. Type: Other.
Transcriptome-wide RNA structure probing reveals the structural basis of Dicer binding and cleavage
GEO Series GSE146952. Homo sapiens. 34 samples. Type: Other.
RNA structure probing to characterize RNA-protein interations on a low abundance pre-mRNA in living cells
GEO Series GSE159719. Mus musculus. 13 samples. Type: Other.
Auroral Spatial Structures Probe Project
<p> &nbsp;</p> <p align="center"> &nbsp;<strong><u>Methodology </u></strong></p> <p> Fly a high altitude sounding rocket with multiple sub-payloads to measure electric and magnetic fields during an auroral event. Use ground based observations to observe winds and conductivities in the ionosphere.</p> <p> The Auroral Spatial Structures Probe (ASSP) is a NASA sounding rocket mission that, will be used to <a href="http://adsabs.harvard.edu/abs/2011AGUFMSA31A1959S" id="_GPLITA_0" in_rurl="http://i.trkjmp.com/click?v=VVM6MzYxMzI6MjE1NTpzdHVkeTo2M2Y3MDQyYTE2ZTU0YTE5N2Q3OTVmNjk3ZWVhNmQwMjp6LTEwNDEtMTA3NTUzOmFkc2Ficy5oYXJ2YXJkLmVkdTozOTQ1NjpmYTVkMTdiYzQzNjMxMGQxNjJlYTMxYmFmYzZhN2MzMQ" title="Click to Continue &gt; by Text-Enhance">study</a> both the spatial and temporal small scale variation of the E-fields during breakup aurora and geomagnetically active conditions. This will be accomplished through the use of a constellation of small payloads that separate relative to each other throughout a sounding rocket flight. The multiple baseline observations of the electric and magnetic fields will be used to observe variability of both the E-field and the Poynting flux. These observations will be placed in the context of available data, including winds, large scale E-fields, and proxy conductivity (airglow images) observations. In this way we will address the main scientific objective of this mission which is: What are the contributions of small spatial scale and rapid temporal scale fluctuations of electric fields relative to the larger-scale electrodynamic processes? The high altitude rocket will be launched along the magnetic field line and carry six sub-payloads to be ejected from the main payload at high velocity. The sub-payloads will be deployed both along the flight path and perpendicular to the flight path so that both spatial features and temporal-spatial ambiguities can be explored. The low-mass sub-payloads that, for a fixed ejection impulse will achieve at least a 50 km separation by the end of the flight are key to the observational success. Each sub-payload will carry a crossed pair of double-probe sensors to measure in-situ electric fields, a three axis magnetometer, a Langmuir probe and a GPS receiver. In this poster we review the ASSP science and mission concepts.</p> <p> &nbsp;</p> <p> &nbsp;</p>
Lead-seq: transcriptome-wide in vivo structure probing with lead
GEO Series GSE140649. Yersinia pseudotuberculosis. 4 samples. Type: Expression profiling by high throughput sequencing.
robust statistical modeling improves sensitivity of high-throughput rnA structure probing experiments
GEO Series GSE78208. Saccharomyces cerevisiae. 4 samples. Type: Other.
Template switching enables chemical probing of native RNA structures
GEO Series GSE274121. Listeria monocytogenes. 18 samples. Type: Other.
Probing Xist RNA structure in cells using Targeted Structure-Seq
GEO Series GSE67667. Mus musculus. 13 samples. Type: Other.
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.