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.
1,487
datasets available to search
ShareScore release 0.9.0
Dataset results
1,487 results for “tagging”
H3K18la marks active tissue-specific enhancers [Cut & Tag human]
GEO Series GSE195854. Homo sapiens. 10 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
ChIP-chip from HEK293-RPF-1 stable transfectants expressing the HA-tagged RPF-1 transcription factor
GEO Series GSE55270. Homo sapiens. 4 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Automated CUT&Tag profiling of chromatin heterogeneity in mixed-lineage leukemia
GEO Series GSE159608. Homo sapiens. 419 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Proteome-scale tagging and functional screening in mammalian cells by ORFtag [PRO-Seq]
GEO Series GSE240285. Mus musculus. 4 samples. Type: Other.
Inhibition of CDK8/CDK19 with the small molecule inhibitor SEL120-34A in prostate cancer cell lines (3’ tag DGE)
GEO Series GSE269071. Homo sapiens. 14 samples. Type: Expression profiling by high throughput sequencing.
Epitope tagging with genome editing in mice reveals that the proton channel OTOP1 is apically localized and not restricted to Type III “sour” taste receptor cells
GEO Series GSE278625. Mus musculus. 1 samples. Type: Expression profiling by high throughput sequencing.
CUT-TAG for AML cell lines
GEO Series GSE246200. Homo sapiens. 8 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Water tagging experiments for the interpretation of Asian speleothem d18O
<p>These simulation results are from the water-tagging experiments in the paper "Deciphering Oxygen Isotope Records From Chinese Speleothems With an Isotope‐Enabled Climate Model" published on Paleoceanography and Paleoclimatology (<a href="https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2019PA003741">https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2019PA003741</a>). Readme.txt provides detailed descriptions of variables in all NetCDF files, and tagging_region_names.pdf shows the abbreviations of all tagging region names. </p>
Fig. 1 in An external tag for fish: tagging effects in different fish size classes and its influence on growth performance and hematology of Lophiosilurus alexandri (Siluriformes: Pseudopimelodidae)
Fig. 1. Visual tag for fish described in the patent BR1020170075770.
Tagged formatted datasets for 'Genetically Optimized Massively Parallel Binary Neural Networks for Intrusion Detection Systems'
<p>Tagged formatted datasets used in 'Genetically Optimized Massively Parallel Binary Neural Networks for Intrusion Detection Systems' T.Murovič, A.Trost.</p>
Tokenized and POS-Tagged Khmer Data of the Asian Language Treebank Project
<p>* Introduction</p> <p>This is the Khmer ALT of the Asian Language Treebank (ALT) Corpus. English texts sampled from English Wikinews were available under a Creative Commons Attribution 2.5 License.</p> <p>Please refer to<br> http://www2.nict.go.jp/astrec-att/member/mutiyama/ALT/index.html<br> for an introduction of the ALT project.</p> <p>Khmer ALT has been developed by NICT and NIPTICT. The license of Khmer ALT is</p> <p>Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) License<br> https://creativecommons.org/licenses/by-nc-sa/4.0/</p> <p><br> * Contents</p> <p>- data_km.km-[tok|tag].nova : tokenized/POS-tagged Khmer sentences by the nova annotation system<br> # based on the following two guildelines<br> # http://www2.nict.go.jp/astrec-att/member/mutiyama/ALT/Khmer-annotation-guideline.pdf<br> # http://www2.nict.go.jp/astrec-att/member/mutiyama/ALT/Khmer-annotation-guideline-supplementary.pdf</p> <p><br> * Disclaimer</p> <p>[1] The content of the selected English Wikinews articles have been translated for this corpus. English texts sampled from English Wikinews were available under a Creative Commons Attribution 2.5 License. Users of the corpus are requested to take careful consideration when encountering any instances of defamation, discriminatory terms, or personal information that might be found within the corpus. Users of the corpus are advised to read Terms of Use in https://en.wikinews.org/wiki/Main_Page carefully to ensure proper usage.</p> <p>[2] NICT bears no responsibility for the contents of the corpus and the lexicon and assumes no liability for any direct or indirect damage or loss whatsoever that may be incurred as a result of using the corpus or the lexicon.</p> <p>[3] If any copyright infringement or other problems are found in the corpus or the lexicon, please contact us at alt-info[at]khn[dot]nict[dot]go[dot]jp. We will review the issue and undertake appropriate measures when needed.</p>
Data from: Modular tagging of amplicons using a single PCR for high-throughput sequencing
High-throughput sequencing (HTS) of PCR amplicons is becoming the method of choice to sequence one or several targeted loci for phylogenetic and DNA barcoding studies. Although the development of HTS has allowed rapid generation of massive amounts of DNA sequence data, preparing amplicons for HTS remains a rate-limiting step. For example, HTS platforms require platform-specific adapter sequences to be present at the 5′ and 3′ end of the DNA fragment to be sequenced. In addition, short multiplex identifier (MID) tags are typically added to allow multiple samples to be pooled in a single HTS run. Existing methods to incorporate HTS adapters and MID tags into PCR amplicons are either inefficient, requiring multiple enzymatic reactions and clean-up steps, or costly when applied to multiple samples or loci (fusion primers). We describe a method to amplify a target locus and add HTS adapters and MID tags via a linker sequence using a single PCR. We demonstrate our approach by generating reference sequence data for two mitochondrial loci (COI and 16S) for a diverse suite of insect taxa. Our approach provides a flexible, cost-effective and efficient method to prepare amplicons for HTS.
Data from: Tracking marine mammals in 3D using electronic tag data
1. Information about at-depth behaviour of marine mammals is fundamental yet very hard to obtain from direct visual observation. Animal-borne multisensor electronic tags provide a unique window of observation into such behaviours. 2. Electronic tag sensors allow the estimation of the animal's 3-dimensional (3D) orientation, depth and speed. Using tag flow noise level to provide an estimate of animal speed, we extend existing approaches of 3D track reconstruction by allowing the direction of movement to differ from that of the animal's longitudinal axis. 3. Data are processed by a hierarchical Bayesian model that allows processing of multisource data, accounting for measurement errors and testing hypotheses about animal movement by comparing models. 4. We illustrate the approach by reconstructing the 3D track of a 52-min deep dive of a Blainville's beaked whale Mesoplodon densirostris adult male fit with a digital tag (DTAG) in the Bahamas. At depth, the whale alternated regular movements at large speed (>1·5 m s -1) and more complex movements at lower speed (<1·5m s-1) with differences between movement and longitudinal axis directions of up to 28inline image. The reconstructed 3D track agrees closely with independent acoustic-based localizations. 5. The approach is potentially applicable to study the underwater behaviour (e.g. response to anthropogenic disturbances) of a wide variety of species of marine mammals fitted with triaxial magnetometer and accelerometer tags.
LLPS REDIFINE allows the biophysical characterization of multicomponent condensates without tags or labels
<p>UPDATE - v3 contains additional jacobianest.m function</p> <p>This zip folder contains the latest NMR data acquired using LLPS REDIFINE method for biomolecular condensates characterization. The Matlab codes are also included.</p>
An Investigation On The Use Of Au@SiO2@Au Nanomatryoshkas As Gap Enhanced Raman Tags Dataset
<p>Gap-enhanced Raman tags are a new type of optical probe that have wide applications in sensing and detection. A gap-enhanced Raman tag is prepared by embedding Raman molecules inside a gap between two plasmonic metals such as an Au core and Au shell. Even though placing Raman tags beneath an Au shell seems counter-intuitive, it has been shown that such systems produce a stronger surface-enhanced Raman scattering response due to the strong electric field inside the gap. While the theoretical support of the stronger electric field inside the gap was provided in the literature, a comprehensive understanding of how the electric field inside the gap compares with that of the outer surface of the particle was not readily available. We investigated Au@SiO$_2$@Au nanoparticles with diameters ranging from 35 nm to 70 nm with varying shell (2.5--10 nm) and gap (2.5--15 nm) thicknesses and obtained both far-field and near-field spectra. The extinction spectra from these particles always have two peaks. The low-energy peak redshifts with the decreasing shell thickness. However, when the gap thickness decreases, the low-energy peaks first blueshift and then redshift, producing a C-shape in the peak position. For every system we investigated, the near-field enhancement spectra were stronger inside the gap than on the outer surface of the nanoparticle. We find that a thin shell combined with a thin gap will produce the greatest near-field enhancement inside the gap. Our work fills the knowledge gap between the exciting potential applications of gap-enhanced Raman tags and the fundamental knowledge of enhancement provided by the gap.</p>
Dataset of Expressed Sequence Tags for Arabian Camel
<p>The dataset consists of 23,602 expressed sequence tags (ESTs) from the Arabian camel. This dataset was made available as part of an effort to undertake a comprehensive re-annotation by leveraging the latest genomic databases and advanced bioinformatics tools. Our primary aim is to uncover potentially novel sequences to gain fresh genetic insights and expand our understanding of camel genetics. This research underscores the importance of revisiting genomic data and demonstrates how advancements in science and technology can significantly contribute to the fields of evolutionary biology and genomics. Through this reevaluation, we identified 2,648 potential novel ESTs, thereby enriching the genetic framework of the Arabian camel and offering new perspectives on its evolutionary characteristics.</p>
VC975 tag-336(ok1477)V | 2010-03-30T14:42:57+01:00
<blockquote> <p>This experiment is part of the <em>C.elegans behavioural database</em>. For more information and the complete collection of experiments visit http://movement.openworm.org</p> </blockquote> <ul> <li><b>preview link</b> : https://www.youtube.com/watch?v=rX0auiKsY8o</li> <li><b>strain</b> : VC975</li> <li><b>timestamp</b> : 2010-03-30T14:42:57+01:00</li> <li><b>gene</b> : tag-336</li> <li><b>chromosome</b> : V</li> <li><b>allele</b> : ok1477</li> <li><b>strain_description</b> : tag-336(ok1477)V</li> <li><b>sex</b> : hermaphrodite</li> <li><b>stage</b> : adult</li> <li><b>ventral_side</b> : anticlockwise</li> <li><b>media</b> : NGM agar low peptone</li> <li><b>arena</b> : <ul> <li><b>style</b> : petri</li> <li><b>size</b> : 35</li> <li><b>orientation</b> : away</li> </ul> </li> <li><b>food</b> : OP50</li> <li><b>habituation</b> : 30m wait</li> <li><b>who</b> : Laura Grundy</li> <li><b>protocol</b> : Method in E. Yemini et al. doi:10.1038/nmeth.2560. Worm transferred to arena 30 minutes before recording starts.</li> <li><b>lab</b> : <ul> <li><b>name</b> : William R Schafer</li> <li><b>location</b> : MRC Laboratory of Molecular Biology, Hills Road, Cambridge, CB2 0QH, UK</li> </ul> </li> <li><b>software</b> : <ul> <li><b>name</b> : tierpsy (https://github.com/ver228/tierpsy-tracker)</li> <li><b>version</b> : cbfc23eb4f1ac2f29be75ade7a937eed58a5b219</li> <li><b>featureID</b> : @OMG</li> </ul> </li> <li><b>base_name</b> : tag-336 (ok1477) on food R_2010_03_30__14_42_57___1___6</li> <li><b>total time (s)</b> : 898.323</li> <li><b>frames per second</b> : 25.5754</li> <li><b>video micrometers per pixel</b> : 4.29558</li> <li><b>number of segmented skeletons</b> : 19668</li> </ul>
VC975 tag-336(ok1477)V | 2010-03-31T12:34:05+01:00
<blockquote> <p>This experiment is part of the <em>C.elegans behavioural database</em>. For more information and the complete collection of experiments visit http://movement.openworm.org</p> </blockquote> <ul> <li><b>preview link</b> : https://www.youtube.com/watch?v=NtfJRRHcssI</li> <li><b>strain</b> : VC975</li> <li><b>timestamp</b> : 2010-03-31T12:34:05+01:00</li> <li><b>gene</b> : tag-336</li> <li><b>chromosome</b> : V</li> <li><b>allele</b> : ok1477</li> <li><b>strain_description</b> : tag-336(ok1477)V</li> <li><b>sex</b> : hermaphrodite</li> <li><b>stage</b> : adult</li> <li><b>ventral_side</b> : anticlockwise</li> <li><b>media</b> : NGM agar low peptone</li> <li><b>arena</b> : <ul> <li><b>style</b> : petri</li> <li><b>size</b> : 35</li> <li><b>orientation</b> : away</li> </ul> </li> <li><b>food</b> : OP50</li> <li><b>habituation</b> : 30m wait</li> <li><b>who</b> : Laura Grundy</li> <li><b>protocol</b> : Method in E. Yemini et al. doi:10.1038/nmeth.2560. Worm transferred to arena 30 minutes before recording starts.</li> <li><b>lab</b> : <ul> <li><b>name</b> : William R Schafer</li> <li><b>location</b> : MRC Laboratory of Molecular Biology, Hills Road, Cambridge, CB2 0QH, UK</li> </ul> </li> <li><b>software</b> : <ul> <li><b>name</b> : tierpsy (https://github.com/ver228/tierpsy-tracker)</li> <li><b>version</b> : cbfc23eb4f1ac2f29be75ade7a937eed58a5b219</li> <li><b>featureID</b> : @OMG</li> </ul> </li> <li><b>base_name</b> : tag-336 (ok1477) on food R_2010_03_31__12_34_05___8___6</li> <li><b>total time (s)</b> : 899.368</li> <li><b>frames per second</b> : 25.7069</li> <li><b>video micrometers per pixel</b> : 4.20853</li> <li><b>number of segmented skeletons</b> : 19609</li> </ul>
VC975 tag-336(ok1477)V | 2010-03-31T12:34:50+01:00
<blockquote> <p>This experiment is part of the <em>C.elegans behavioural database</em>. For more information and the complete collection of experiments visit http://movement.openworm.org</p> </blockquote> <ul> <li><b>preview link</b> : https://www.youtube.com/watch?v=QjlIL9B8Kkk</li> <li><b>strain</b> : VC975</li> <li><b>timestamp</b> : 2010-03-31T12:34:50+01:00</li> <li><b>gene</b> : tag-336</li> <li><b>chromosome</b> : V</li> <li><b>allele</b> : ok1477</li> <li><b>strain_description</b> : tag-336(ok1477)V</li> <li><b>sex</b> : hermaphrodite</li> <li><b>stage</b> : adult</li> <li><b>ventral_side</b> : anticlockwise</li> <li><b>media</b> : NGM agar low peptone</li> <li><b>arena</b> : <ul> <li><b>style</b> : petri</li> <li><b>size</b> : 35</li> <li><b>orientation</b> : away</li> </ul> </li> <li><b>food</b> : OP50</li> <li><b>habituation</b> : 30m wait</li> <li><b>who</b> : Laura Grundy</li> <li><b>protocol</b> : Method in E. Yemini et al. doi:10.1038/nmeth.2560. Worm transferred to arena 30 minutes before recording starts.</li> <li><b>lab</b> : <ul> <li><b>name</b> : William R Schafer</li> <li><b>location</b> : MRC Laboratory of Molecular Biology, Hills Road, Cambridge, CB2 0QH, UK</li> </ul> </li> <li><b>software</b> : <ul> <li><b>name</b> : tierpsy (https://github.com/ver228/tierpsy-tracker)</li> <li><b>version</b> : cbfc23eb4f1ac2f29be75ade7a937eed58a5b219</li> <li><b>featureID</b> : @OMG</li> </ul> </li> <li><b>base_name</b> : tag-336 (ok1477) on food R_2010_03_31__12_34_50__6</li> <li><b>total time (s)</b> : 899.345</li> <li><b>frames per second</b> : 25.7732</li> <li><b>video micrometers per pixel</b> : 4.3011</li> <li><b>number of segmented skeletons</b> : 19952</li> </ul>
VC975 tag-336(ok1477)V | 2010-03-31T12:32:41+01:00
<blockquote> <p>This experiment is part of the <em>C.elegans behavioural database</em>. For more information and the complete collection of experiments visit http://movement.openworm.org</p> </blockquote> <ul> <li><b>preview link</b> : https://www.youtube.com/watch?v=9qGbd0nJrlM</li> <li><b>strain</b> : VC975</li> <li><b>timestamp</b> : 2010-03-31T12:32:41+01:00</li> <li><b>gene</b> : tag-336</li> <li><b>chromosome</b> : V</li> <li><b>allele</b> : ok1477</li> <li><b>strain_description</b> : tag-336(ok1477)V</li> <li><b>sex</b> : hermaphrodite</li> <li><b>stage</b> : adult</li> <li><b>ventral_side</b> : anticlockwise</li> <li><b>media</b> : NGM agar low peptone</li> <li><b>arena</b> : <ul> <li><b>style</b> : petri</li> <li><b>size</b> : 35</li> <li><b>orientation</b> : away</li> </ul> </li> <li><b>food</b> : OP50</li> <li><b>habituation</b> : 30m wait</li> <li><b>who</b> : Laura Grundy</li> <li><b>protocol</b> : Method in E. Yemini et al. doi:10.1038/nmeth.2560. Worm transferred to arena 30 minutes before recording starts.</li> <li><b>lab</b> : <ul> <li><b>name</b> : William R Schafer</li> <li><b>location</b> : MRC Laboratory of Molecular Biology, Hills Road, Cambridge, CB2 0QH, UK</li> </ul> </li> <li><b>software</b> : <ul> <li><b>name</b> : tierpsy (https://github.com/ver228/tierpsy-tracker)</li> <li><b>version</b> : cbfc23eb4f1ac2f29be75ade7a937eed58a5b219</li> <li><b>featureID</b> : @OMG</li> </ul> </li> <li><b>base_name</b> : tag-336 (ok1477) on food R_2010_03_31__12_32_41___6___6</li> <li><b>total time (s)</b> : 898.792</li> <li><b>frames per second</b> : 25.5754</li> <li><b>video micrometers per pixel</b> : 4.33523</li> <li><b>number of segmented skeletons</b> : 19334</li> </ul>
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.