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7,195 results for “SET”
A Pseudonymized Rehydrated Tweets Data Set collected before and after the Onset of the War between Russia and Ukraine in 2022
<p>Related to our other dataset publication, which can be found <a href="https://zenodo.org/record/6381899#.Yj1mCy8w2J8">here</a>, we publish the pseudonymized texts of the tweets no longer available after the rehydration process via Twitter's historic search API. Please note that we restrict access to these datasets to specific parties under certain conditions, as can be seen below. </p> <p>The datasets contain the timestamps of the tweets, the pseudonymized full text, as well as the time of rehydration. </p> <p>If you gain access to this dataset, please cite our paper: </p> <blockquote> <p>Pohl, Janina Susanne and Seiler, Moritz Vinzent and Assenmacher, Dennis and Grimme, Christian, A Twitter Streaming Dataset collected before and after the Onset of the War between Russia and Ukraine in 2022 (March 25, 2022). Available at SSRN: <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4066543">https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4066543</a></p> </blockquote>
Hateful Messages: A Conversational Data Set of Hate Speech produced by Adolescents on Discord
<p>With the rise of social media, a rise of hateful content can be observed. Even though the understanding and definitions of hate speech varies, platforms, communities, and legislature all acknowledge the problem. Therefore, adolescents are a new and active group of social media users. The majority of adolescents experience or witness online hate speech. Research in the field of automated hate speech classification has been on the rise and focuses on aspects such as bias, generalizability, and performance. To increase generalizability and performance, it is important to understand biases within the data. This research addresses the bias of youth language within hate speech classification and contributes by providing a modern and anonymized hate speech youth language data set consisting of 88.395 annotated chat messages. The data set consists of publicly available online messages from the chat platform Discord. ~6,42\% of the messages were classified by a self-developed annotation schema as hate speech. For 35.553 messages, the user profiles provided age annotations setting the average author age to under 20 years old.</p>
Data Sets of Timing and Kinematics of Late Cenozoic Strike-slip Faults in Western Tibetan Plateau: New Constraints from Provenance Analysis and Detrital Thermochronology
<p>Data Sets of Wei et al. (2023). The manuscript is titled Timing and Kinematics of Late Cenozoic Strike-slip Faults in Western Tibetan Plateau: New Constraints from Provenance Analysis and Detrital Thermochronology</p>
Paladino et al., 2024 raw PCM output Set # 2
<p>Set #2 of PCM output from Paladino et al., (2024).</p>
Paladino et al., 2024 raw PCM output Set # 1
<p>Set #1 of PCM output from Paladino et al., (2024).</p>
Korean Colorectal Cancer Cohort RNA-seq data set from Asan Medical Center
<p>This study presents a comprehensive molecular analysis of colorectal cancer (CRC) in Korean patients using RNA-sequencing data and clinical information. Key findings include significant differences in gene expression between tumor and normal tissues and identification of dysregulated pathways related to tumor progression. CRC samples were stratified into molecular subtypes, confirming their similarity to established CRC classifications. Immunological analysis highlighted distinguishing features between tumor and normal tissues, and some patients were found to be responsive to immunotherapy, especially those with microsatellite stable (MSS) tumors, who demonstrated a better prognosis. These insights enhance the understanding of CRC in Korean patients and support the use of RNA-seq data to inform cancer treatment and improve patient care.</p>
Korean Colorectal Cancer Cohort RNA-seq data set from Seoul National University Bundang Hospital and Uijeongbu St. Mary's Hospital
<p>Colorectal cancer (CRC) is a leading cause of cancer-related mortality worldwide, and understanding the molecular mechanisms underlying CRC development and progression is critical for developing effective treatments. In this study, we performed RNA sequencing (RNA-seq) analysis of CRC tissue samples and adjacent normal tissue samples from 384 cohort to investigate differential gene expression between the two groups. We identified a total of 19,635 expressed genes in CRC tissue and normal tissue, with 3,816 differentially expressed genes (DEGs) identified between the two groups. Functional annotation analysis revealed that upregulated DEGs were significantly enriched in pathways related to cell cycle, DNA replication, and IL-17, while downregulated DEGs were enriched in metabolic pathways. We also analyzed relationships between the clinical information and subtypes using Consensus Molecular Subtype (CMS). Our findings provide valuable insights into the molecular mechanisms underlying Korean CRC patients and suggest potential targets for developing new treatments for this deadly disease. The raw data and processed results of this study have been deposited in a public repository to enable further analysis and exploration.</p> <p>Please cite the original article:</p>
Data set for Persistent LBP study
<p>Raw data for the study 'Prevalence and characteristics of women with persistent LBP postpartum'</p>
WRF-Chem configurations and input data sets for sensitivity tests of emission inventories
<p>WRF-Chem and WPS v4.4 source codes and their configurations with namelist files.</p> <p>Emission inventory data sets (EDGAR-HTAP v2 and v3) for 'anthro_emis' input are included.</p> <p>The KORUS v5 emission data are provided with 'wrfchemi' format.</p> <p>The 'namelist.input' contains physics and chemistry options that are used for WRF-Chem model.</p> <p>The model grid information is available in 'namelist.wps'.</p> <p> </p> <p>Kim, K.-M., Kim, S.-W., Seo, S., Blake, D. R., Cho, S., Crawford, J. H., Emmons, L., Fried, A., Herman, J. R., Hong, J., Jung, J., Pfister, G., Weinheimer, A. J., Woo, J.-H., and Zhang, Q.: Sensitivity of the WRF-Chem v4.4 ozone, formaldehyde, and precursor simulations to multiple bottom-up emission inventories over East Asia during the KORUS-AQ 2016 field campaign, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2023-132, in review, 2023.</p>
SCANS Data Set - A Reference Data Set for Handwritten Text Detection
<p># SCANS Data Set<br> <br> A scientific paper with handwritten annotations as reference data set for handwritten text detection.<br> <br> The paper is</p> <pre><code>Sharon Fogel, Hadar Averbuch-Elor, Sarel Cohen, Shai Mazor, Roee Litman; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recogniti on (CVPR), 2020, pp. 4324-4333</code></pre> <p><br> The annotations were made by two people with different pens. The text is randomly taken from "The Fellowship Of The Ring" by JRR Tolkien.<br> <br> The documents in folder `images` were scanned with a Canon Pixima TR4550 with 300DPI. The `labels-` folders contain the labels for paragraph, line, and word level in following JSON format:<br> </p> <pre><code>{ "image_file": "paper-0001.png", # The corresponding image in folder `images` "shape": [ # The size of the image 3495, 2473 ], "properties": [ # A list of all line bounding boxes (for paragraphs, lines, or words) { "type": "HWL", # HWA: handwritten paragraph, HWL: handwritten line, HWW: handwritten word "id": "18", "points": [ # The coordinates of the bounding boxes [ 1243.87096093748, 1515.21674083916 ], [ 2149.01588303892, 1515.21674083916 ], ... ] }, ... ] }</code></pre> <p> </p>
α-linolenic acid and long-chain n-3 polyunsaturated fatty acids modulate colitis operating with a different gene set
GEO Series GSE76331. Rattus norvegicus. 8 samples. Type: Expression profiling by array.
Dynamic rewiring of transcription factor networks during smooth muscle cell phenotypic modulation (RNA-Seq data sets)
GEO Series GSE111714. Rattus norvegicus. 14 samples. Type: Expression profiling by high throughput sequencing.
Profiling of Salivary Exosomal microRNAs in Oral Lichen Planus Patients [set 1]
GEO Series GSE68406. Homo sapiens. 2 samples. Type: Non-coding RNA profiling by array.
Selective lymphoma cell killing by a PRC2 small molecule inhibitor (ChIP-Seq set 2)
GEO Series GSE40473. Homo sapiens. 8 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
A three lncRNA set: AC009975.1, POTEH-AS1 and AL390243.1 as nodal efficacy biomarker of neoadjuvant therapy for HER-2 positive breast cancer
GEO Series GSE188743. Homo sapiens. 6 samples. Type: Non-coding RNA profiling by array.
Identification of lineage-specific transcription factors setting the active distal regulatory landscape that drives astrogliogenesis
GEO Series GSE96539. Mus musculus. 51 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Transcript profiling reveals a molecular signature that distinguishes early versus late time to bud set phenotypes in a white spruce full-sib family.
GEO Series GSE57172. Picea sitchensis; Picea glauca. 4 samples. Type: Expression profiling by array.
Comparative RNA sequencing-based transcriptome profiling of ten grapevine rootstocks: shared and specific sets of genes respond to mycorrhizal symbiosis
GEO Series GSE234583. Vitis vinifera. 60 samples. Type: Expression profiling by high throughput sequencing.
Gene expression in healthy and lesional psoriatic dermis from human skin biopsies (laser capture microdissection): set 1
GEO Series GSE68924. Homo sapiens. 5 samples. Type: Expression profiling by array.
Evolutionary transcriptomics of Eutherian gene expression gains and the origins of decidualization [Set 3]
GEO Series GSE189448. Homo sapiens. 56 samples. Type: Expression profiling by high throughput sequencing.
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.