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1,454
datasets available to search
ShareScore release 0.9.0
Dataset results
1,454 results for “large scale”
Global analysis reveals large scale dynamics of protein-RNA interaction and RNA secondary structure characteristics of Physcomitrella patens ABA response (PIP-Seq)
GEO Series GSE148423. Physcomitrium patens. 24 samples. Type: Other.
Calcineurin inhibitor-induced renal side effects – Identification of underlying molecular mechanism via transcriptional analysis on large-scale isolated renal tubules
GEO Series GSE169721. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing.
MYC activation and BCL2L11 silencing by a tumor virus through the large-scale reconfiguration of enhancer-promoter hubs [EREB]
GEO Series GSE82149. Homo sapiens. 4 samples. Type: Other.
miR profile in pagetic osteoclasts: from large-scale sequencing to gene expression study
GEO Series GSE174180. Homo sapiens. 18 samples. Type: Expression profiling by high throughput sequencing.
Large scale transcriptomic characterization of mice blood inflammation during Acute Lung Injury (PBMC)
GEO Series GSE52684. Mus musculus. 30 samples. Type: Expression profiling by array.
Large-scale discovery of potent, compact and lineage specific enhancers for gene therapy vectors [RNA-seq]
GEO Series GSE252161. Homo sapiens. 16 samples. Type: Expression profiling by high throughput sequencing.
Large-scale genomic alterations identified in cancer patients on the course of cancer recovery with complementary Huaier treatment identified by total RNA- and small non-coding RNA-sequencing.
GEO Series GSE157086. Homo sapiens. 184 samples. Type: Expression profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing.
Integrating a genome-wide association study with a large-scale transcriptome analysis to predict genetic regions influencing the glycemic index and texture in rice
GEO Series GSE123616. Oryza sativa Indica Group. 21 samples. Type: Expression profiling by array.
MYC activation and BCL2L11 silencing by a tumor virus through the large-scale reconfiguration of enhancer-promoter hubs [Bcell]
GEO Series GSE82148. Homo sapiens. 6 samples. Type: Other.
Global analysis reveals large scale dynamics of protein-RNA interaction and RNA secondary structure characteristics of Physcomitrella patens ABA response (mRNA)
GEO Series GSE148422. Physcomitrium patens. 6 samples. Type: Expression profiling by high throughput sequencing.
EID1 knochdown by small RNA induces the large-scale conversion of adipose-derived mesenchymal stem cells into hematopoietic stem cells
GEO Series GSE42650. Homo sapiens. 2 samples. Type: Expression profiling by array.
A cost-effective RNA sequencing protocol for large-scale gene expression studies
GEO Series GSE89872. Homo sapiens. 179 samples. Type: Expression profiling by high throughput sequencing.
Large scale transcriptomic characterization of mice brain inflammation during Acute Lung Injury (brain)
GEO Series GSE52683. Mus musculus. 31 samples. Type: Expression profiling by array.
Large scale analysis of leaf gene expression upon treatment of apple grafted scions with acibenzolar-S-methyl or water at 20 or 35°C
GEO Series GSE280234. Malus domestica. 16 samples. Type: Expression profiling by array.
Single-cell analysis of the nervous system at small and large scales with instant partitions.
GEO Series GSE236063. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
Invalid Dataset for "Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior"
<p>This dataset is invalid. <strong>The updated version of this Dataset is here:</strong> <a href="https://zenodo.org/record/3678559#.Xl9-Ji97FhE">https://zenodo.org/record/3678559#.Xl9-Ji97FhE</a></p> <p> </p> <p>Dataset for the "Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior" paper, published in ICWSM 2018. The full text of the paper can be found <a href="https://arxiv.org/pdf/1802.00393.pdf">here</a>. </p> <p>The dataset provided here includes an updated version of the original dataset, with ~100k tweets annotated using the CrowdFlower platform: </p> <ul> <li> <p>hatespeech_labels.csv: contains ~100K rows, where every row consists of a unique Tweet ID and its according to majority annotation </p> </li> </ul> <p>UPDATE: It has come to our understanding that a number of the tweets are not available anymore for download on Twitter. Therefore, under request, we can provide one more file with the full ~100K tweet text, their associated majority label, and the number of votes for the majority label. The tweets are shuffled so that there is no connection between tweet IDs and texts (in order to be in line with the T&C of Twitter). To obtain the file contact the authors through email. </p> <p> </p> <p>Please cite the paper in any published work that uses any of these resources. </p> <p>@inproceedings{founta2018large, <br> title={Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior}, <br> author={Founta, Antigoni-Maria and Djouvas, Constantinos and Chatzakou, Despoina and Leontiadis, Ilias and Blackburn, Jeremy and Stringhini, Gianluca and Vakali, Athena and Sirivianos, Michael and Kourtellis, Nicolas}, <br> booktitle={11th International Conference on Web and Social Media, ICWSM 2018}, <br> year={2018}, <br> organization={AAAI Press} <br> } </p> <p>For any further questions contact a.m.founta at gmail dot com AND markos.charalambous at eecei.cut.ac.cy </p>
Restricted Dataset for "Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior"
<p>Restricted Dataset for the "Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior" paper, published in ICWSM 2018. The full text of the paper can be found <a href="https://arxiv.org/pdf/1802.00393.pdf">here</a>. The Public version of the dataset can be found <a href="https://zenodo.org/record/3678559#.Xk_23y97FhE">here</a></p> <ul> <li> <p>hatespeech_text_label_vote_RESTRICTED_100K.csv: contains ~100K raws with tweet text, the associated majority label, and the number of votes for the majority label. The tweets are shuffled so that there is no connection between tweet IDs and texts (in order to be in line with the T&C of Twitter). </p> </li> <li> <p>retweets.csv: contains ~2K rows, where every row consists of the row number in the hatespeech_text_label_vote_RESTRICTED_100K.csv file which is the first occurrence of a Tweet text followed by comma-separated row numbers of all other occurrences of the same Tweet text in the same file. There are ~8K other occurrences due to retweets. </p> </li> </ul> <p>Please cite the paper in any published work that uses any of these resources. </p> <p>@inproceedings{founta2018large, <br> title={Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior}, <br> author={Founta, Antigoni-Maria and Djouvas, Constantinos and Chatzakou, Despoina and Leontiadis, Ilias and Blackburn, Jeremy and Stringhini, Gianluca and Vakali, Athena and Sirivianos, Michael and Kourtellis, Nicolas}, <br> booktitle={11th International Conference on Web and Social Media, ICWSM 2018}, <br> year={2018}, <br> organization={AAAI Press} <br> } </p> <p>For any further questions contact a.m.founta at gmail dot com AND markos.charalambous at eecei dot cut dot ac dot cy </p>
WALOWA (WAVE LOADS ON WALLS) - LARGE SCALE EXPERIMENTS IN THE DELTA FLUME
<p>WaLoWa stands for Wave Loads on Walls and is a Hydralab+ project funded by the European Union. Ghent University (Belgium), TU Delft (The Netherlands), RWTH Aachen (Germany), Politechnico Bari and University of Florence (Italy) and Flanders Hydraulics Research (Belgium) are jointly working on the WaLoWa project. The user team leader is Ghent University. The WaLoWa project is hosted by Deltares and the Delta Flume facility.</p> <p>When storm walls and buildings are located on top of a dike or promenade, overtopping waves can induce large forces on these structures as has e.g. been observed at the Belgian coast which has a specifically shallow foreshore. Especially during storm season and in times of sea level rise these loads can be highly destructive. It is therefore the key objective of WaLoWa to study overtopped wave loads on structures situated on top of a dike and in shallow foreshore conditions.</p>
Inclusiveness Matters: A Large-Scale Analysis of User Feedback
<p>This dataset includes the user feedback (app reviews, Reddit, and Twitter posts) from 50 popular apps, used in our study on analyzing inclusivenss in user feedback. We also provide the labels for the manually labelled data. In addition, we also provide the memoing for the analysis of the social technical grounded theory process. </p><p> </p>
A large-scale high-resolution cropland non-agriculturalization (Hi-CNA) dataset
<p><span>The Hi-CNA is a high-resolution remote sensing dataset dedicated to the cropland non-agriculturalization (CNA) tasks, featuring high-quality semantic and change annotations for cropland. The study area covers parts of Hebei, Shanxi, Shandong, Hubei provinces in China, with a total area exceeding 1100 km<sup>2</sup>. These regions exhibit significant variations in crop planting, ensuring the diversity of cropland morphologies. The first temporal phase spans from 2015 to 2017, while the second phase ranges from 2020 to 2022, covering multiple phenological periods of crops. These characteristics provide a rich variety of samples for CNA tasks.</span></p> <p><span><span>The dataset is sourced from multispectral GF-2 fusion images with a spatial resolution of 0.8m, encompassing four bands including visible light and near-infrared. All images are cropped to 512*512, resulting in a total of 6797 pairs of dual-temporal images with corresponding annotations. Figure 1 illustrates different forms of cropland and some types of changes.</span></span></p>
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.