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15,733 results for “article”
BreXLiMe: A Semantically Enriched Dataset With News Articles, Micro-Posts, and TV Shows Related to the Brexit
<p>We provide a <strong>large data set of media content metadata</strong> from various media sources (including online news sites, social media, and live-TV) in three languages (<strong>English, German, and Spanish</strong>). Overall, the data set contains rich metadata for about <strong>240 thousand news articles, 12 million micro-posts, and 900 TV shows</strong>. All media content information has been semantically enriched with annotations of both entities and categories from DBpedia.</p> <p>The data can be used as a valuable data basis for applications and studies of various disciplines (e.g., social studies, political science, and humanities) on the case of Brexit, particularly on the <strong>media landscape before the Brexit referendum held on June 23, 2016</strong>.</p> <p>We provide the data set in the RDF serialization format Turtle (.ttl) as well as in XML.</p> <p>If you use our data set, please <strong>cite</strong> it as follows:</p> <pre><code>Lei Zhang, Maribel Acosta, Michael Färber, Steffen Thoma and Achim Rettinger. "BreXearch: Exploring Brexit Data Using Cross-Lingual and Cross-Media Semantic Search". In: Proceedings of the ISWC 2017 Posters & Demonstrations Track within the 16th International Semantic Web Conference (ISWC 2017). Vienna, Austria, 2017.</code></pre> <p> </p>
Data and code related to the article "Characterization of the Log-normal Model for Received Signal Strength Measurements in Real Wireless Sensor Networks"
<p>This upload contains the data and code related to the article "Characterization of the Log-normal Model for Received Signal Strength Measurements in Real Wireless Sensor Networks", (D.O.I: <a href="https://doi.org/10.3390/jsan9010012">10.3390/jsan9010012</a>) published in the the special issue on "Localization in Wireless Sensor Networks" of the <a href="https://www.mdpi.com/journal/jsan"><em>Journal of Sensor and Actuator Networks</em></a> (ISSN 2224-2708).</p> <p>The data and code included allows to replicate the results of the article.</p>
Dataset related to article "TNF-Stimulated Gene-6 Is a Key Regulator in Switching Stemness and Biological Properties of Mesenchymal Stem Cells."
<p>Mesenchymal stem cells (MSCs) are well established to have promising therapeutic properties. TNF-stimulated gene-6 (TSG-6), a potent tissue-protective and anti-inflammatory factor, has been demonstrated to be responsible for a significant part of the tissue-protecting properties mediated by MSCs. Nevertheless, current knowledge about the biological function of TSG-6 in MSCs is limited. Here, we demonstrated that TSG-6 is a crucial factor that influences many functional properties of MSCs. The transcriptomic sequencing analysis of wild-type (WT) and TSG-6<sup>-/-</sup> -MSCs shows that the loss of TSG-6 expression leads to the perturbation of several transcription factors, cytokines, and other key biological pathways. TSG-6<sup>-/-</sup> -MSCs appeared morphologically different with dissimilar cytoskeleton organization, significantly reduced size of extracellular vesicles, decreased cell proliferative rate, and loss of differentiation abilities compared with the WT cells. These cellular effects may be due to TSG-6-mediated changes in the extracellular matrix (ECM) environment. The supplementation of ECM with exogenous TSG-6, in fact, rescued cell proliferation and changes in morphology. Importantly, TSG-6-deficient MSCs displayed an increased capacity to release interleukin-6 conferring pro-inflammatory and pro-tumorigenic properties to the MSCs. Overall, our data provide strong evidence that TSG-6 is crucial for the maintenance of stemness and other biological properties of murine MSCs.</p> <p> </p> <p>Some dataset of this research are in prism format, to ensure open access we attach a pdf instruction about this format and a link where downoladed it</p>
Dataset related to the article "Laboratory-scale hydraulic fracturing dataset for benchmarking of Enhanced Geothermal System simulation tools"
<p>Experimental results from hydraulic fracturing experiments performed in granite and marble samples of size 30 cm × 30 cm × 45 cm under well-defined boundary conditions.</p> <p>Datasets include:</p> <ul> <li>pressure versus flow-rate response</li> <li>acoustic emission data from a dense network of 32 seismic sensors</li> <li>detailed description of the experimental set-up and adopted test protocol</li> <li>mechanical and petrophysical properties of the samples</li> <li>python code for seismic data processing</li> </ul> <p>This complete collection of data, obtained within the framework of European Union’s Horizon 2020 project GEMex, is rare in its kind and indispensable for verification of model assumptions and constitutive relationships of numerical codes used for designing field-scale hydraulic fracturing experiments.</p>
Dataset related to article "NKp46-expressing human gut-resident intraepithelial Vδ1 T cell subpopulation exhibits high antitumor activity against colorectal cancer"
<p>γδ T cells account for a large fraction of human intestinal intraepithelial lymphocytes (IELs) endowed with potent antitumor activities. However, little is known about their origin, phenotype, and clinical relevance in colorectal cancer (CRC). To determine γδ IEL gut specificity, homing, and functions, γδ T cells were purified from human healthy blood, lymph nodes, liver, skin, and intestine, either disease-free, affected by CRC, or generated from thymic precursors. The constitutive expression of NKp46 specifically identifies a subset of cytotoxic Vδ1 T cells representing the largest fraction of gut-resident IELs. The ontogeny and gut-tropism of NKp46+/Vδ1 IELs depends both on distinctive features of Vδ1 thymic precursors and gut-environmental factors. Either the constitutive presence of NKp46 on tissue-resident Vδ1 intestinal IELs or its induced expression on IL-2/IL-15-activated Vδ1 thymocytes are associated with antitumor functions. Higher frequencies of NKp46+/Vδ1 IELs in tumor-free specimens from CRC patients correlate with a lower risk of developing metastatic III/IV disease stages. Additionally, our in vitro settings reproducing CRC tumor microenvironment inhibited the expansion of NKp46+/Vδ1 cells from activated thymic precursors. These results parallel the very low frequencies of NKp46+/Vδ1 IELs able to infiltrate CRC, thus providing insights to either follow-up cancer progression or to develop adoptive cellular therapies.</p> <p> </p> <p>This dataset is created with fcs files form, in order to guarantee the access we attach a pdf information about</p>
A study on article selection behavior - Survey
<p>This survey helped to evaluate the behavior of economists in academia during the article selection process using different scholarly evaluation metrics. Within this survey, we presented both bibliometric and altmetric indicators attached to four journal articles of which the participants were encouraged to make a decision which article they want to read first. This study, however, was focused more on finding out the usefulness of altmetric information when selecting an article for reading rather than the bibliometric indicators in general.</p> <p>The questionnaire is created on the LimeSurvey. It was disseminated to roughly 15,000 economists worldwide, contacted via email addresses found within the mailing list. The distribution of the survey started on November 11, 2019, and was online for three and a half weeks until November 29, 2019. </p> <p> </p> <p> </p>
Datasets for How is the Pandemic Affecting AGU Journal Article Submissions?
<p>These files provide tabular data on gender, age, and country of corresponding authors (the person submitting the manuscript to the peer review system) of American Geophysical Union (AGU) journals from January 2018 through April 2020. They supplement the article 'How is the Pandemic Affecting AGU Journal Article Submissions?' in Eos (https://eos.org/).</p>
Sentiment analysis of tech media articles using VADER package and co-occurrence analysis (01.2016-12.2019)
<p>Sentiment analysis of tech media articles using VADER package and co-occurrence analysis</p> <p>Sources with weights:</p> <ul> <li>Euractiv 5%</li> <li>The Conversation 5%</li> <li>Politico Europe 5 %</li> <li>IEEE Spectrum 5 %</li> <li>Techforge 5%</li> <li>Fastcompany 5%</li> <li>The Guardian (Tech) 12%</li> <li>Arstechnica 5%</li> <li>Reuters 5%</li> <li>Gizmodo 9%</li> <li>ZDNet 9%</li> <li>The Register 12%</li> <li>The Verge 9%</li> <li>TechCrunch 9%</li> </ul> <p>Methodology</p> <p>The sentiment analysis has been prepared using VADER*, an open-source lexicon and rule-based sentiment analysis tool. VADER is specifically designed for social media analysis, but can be also applied for other text sources. The sentiment lexicon was compiled using various sources (other sentiment data sets, Twitter etc.) and was validated by human input. The advantage of VADER is that the rule-based engine includes word-order sensitive relations and degree modifiers.</p> <p>As VADER is more robust in the case of shorter social media texts, the analysed articles have been divided into paragraphs. The analysis have been carried out for the social issues presented in the co-occurrence exercise.</p> <p>The process included the following main steps:</p> <ul> <li>The 100 most frequently co-occurring terms are identified for every social issue (using the co-occurrence methodology)</li> <li>The articles containing the given social issue and co-occurring term are identified</li> <li>The identified articles are divided into paragraphs</li> <li>Social issue and co-occurring words are removed from the paragraph</li> <li>The VADER sentiment analysis is carried out for every identified and modified paragraph</li> <li>The average for the given word pair is calculated for the final result</li> </ul> <p>Therefore, the procedure has been repeated for 100 words for all identified social issues.</p> <p>The sentiment analysis resulted in a compound score for every paragraph. The score is calculated from the sum of the valence scores of each word in the paragraph, and normalised between the values -1 (most extreme negative) and +1 (most extreme positive). Finally, the average is calculated from the paragraph results. Removal of terms is meant to exclude sentiment of the co-occurring word itself, because the word may be misleading, e.g. when some technologies or companies attempt to solve a negative issue. The neighbourhood's scores would be positive, but the negative term would bring the paragraph's score down.</p> <p> </p> <p>*Hutto, C.J. & Gilbert, E.E. (2014). VADER: A Parsimonious Rule-based Model for Sentiment Analysis of Social Media Text. Eighth International Conference on Weblogs and Social Media (ICWSM-14). Ann Arbor, MI, June 2014.</p>
Data and supplementary material in support of article "Can robots express facial emotions dominantly enough for use in dementia care?"
<p>Data and supplementary material in support of article "Vlachos, E. and Tan, Z. H. (2020). Can robots express facial emotions dominantly enough for use in dementia care?, <em>International Psychogeriatrics</em>, Cambridge University Press". </p> <p>Our objective is to evaluate the recognition, and denomination of the six basic emotional facial expressions as displayed by a social robot to persons with dementia, and to compare it with the results from the evaluation of static photographs of humans from the Paul Ekman database in order to investigate the differences in recognition rates among the two stimuli.</p>
Dataset and Simulation Files for article "Alumina coating for dispersion management in ultra-high Q microresonators"
<p>Link to arXiv submission: <a href="https://arxiv.org/abs/2009.07826">https://arxiv.org/abs/2009.07826</a></p> <ul> <li>Figure 1 <ul> <li>Data, Jupyter scripts, and comsol simulations files for parts (d,e)</li> <li>Data, Jupyter scripts, and simulations files for parts (f,g,h)</li> </ul> </li> <li>Figure 2 <ul> <li>Raw AFM data for use in Gwydeon software</li> <li>Data, Jupyter scripts, and comsol simulations files for parts (d,e)</li> </ul> </li> <li>Figure 3 <ul> <li>Raw data and Jupyter processing scripts for transmission spectrum calibration (parts - b)</li> <li>Frequency calibrated transmission spectrum and GVD/ Quality factor Jupyter scripts (parts d-g)</li> </ul> </li> <li>Figure 4 <ul> <li>Experimental data for parts a-g</li> </ul> </li> <li>Supplementary data <ul> <li>Raw ellipsometer data</li> <li>1D COMSOL FEM solver and analytical validation (including Julia Jupyter script)</li> <li>Quality factor estimation based on scattering and water adsorption</li> </ul> </li> </ul>
MIDAS hand-annotated news articles
<p>This dataset was produced in 2020 from the data collected throughout 2019 for the development of the MIDAS project (http://www.midasproject.eu/)</p> <p>The data is distributed throughout 5 topics:</p> <p>- EUS: Childhood Obesity (UC Basque Country)<br> - FIN: Mental Health (UC Finland)<br> - IRE: Diabetes (UC Ireland)<br> - NIR: Children in Care (UC Northern Ireland)<br> - INF: Infectious Diseases including Coronavirus (UC Influenzanet)</p> <p>The available data comes in 3 kinds and file formats:</p> <p>TXT - the source of news including ID, title and body of text<br> CSV - the hand annotation of the news articles in TXT with 5 to 10 MeSH headings<br> JSON - the input file for the evaluation of the classifier, including the title, news article body and MeSH heading IDs (available from https://www.ncbi.nlm.nih.gov/mesh/)</p> <p>The CSV files with name starting in "f1_", "pr_", "re_" are the results of the F1/Precision/Recall evaluation for each of the cases.</p> <p>## AUTHORS</p> <p>Joao Pita Costa, Anthony Staines, Jarmo Pääkkönen, Jenni Konttila, Joseba Bidaurrazaga, Oihana Belar, Christine Henderson</p> <p>## ACKNOWLEDGMENTS</p> <p>This work was supported by the European Commission H2020 project MIDAS (G.A. nr. 727721). </p> <p><br> ## LICENSE</p> <p>This dataset is licensed over Creative Commons.</p>
Datasets from the RecSys 2020 article "Carousel Personalization in Music Streaming Apps with Contextual Bandits"
<p>We publicly release the anonymized <em>user_features.csv</em> and <em>playlist_features.csv</em> datasets, from the music streaming platform Deezer, as described in the article "<em>Carousel Personalization in Music Streaming Apps with Contextual Bandits"</em> published in the proceedings of the 14th ACM Conference on Recommender Systems (<em>RecSys 2020</em>). The paper is available <a href="https://arxiv.org/abs/2009.06546">here</a>.</p> <p>These datasets are used in the GitHub repository <a href="https://github.com/deezer/carousel_bandits">deezer/carousel_bandits</a> to reproduce experiments from the article.</p> <p>Please cite our paper if you use our code or data in your work.</p>
Data and simulations files for the article "Quasinormal-mode perturbation theory for dissipative and dispersive optomechanics".
<p>Data and simulations files for the article "Quasinormal-mode perturbation theory for dissipative and dispersive optomechanics".</p>
Dataset and trained models belonging to the article 'Distant reading patterns of iconicity in 940.000 online circulations of 26 iconic photographs'
<p>Quantifying Iconicity - Zenodo</p> <p><br> ## The Dataset<br> This dataset contains the material collected for the article "Distant reading 940,000 online circulations of 26 iconic photographs" (to be) published in New Media & Society (DOI: 10.1177/14614448211049459). We identified 26 iconic photographs based on earlier work (Van der Hoeven, 2019). The Google Cloud Vision (GCV) API was subsequently used to identify webpages that host a reproduction of the iconic image. The GCV API uses computer vision methods and the Google index to retrieve these reproductions. The code for calling the API and parsing the data can be found on GitHub: https://github.com/rubenros1795/ReACT_GCV.</p> <p>The core dataset consists of .tsv-files with the URLs that refer to the webpages. Other metadata provided by the GCV API is also found in the file and manually generated metadata. This includes:<br> - the URL that refers specifically to the image. This can be an URL that refers to a full match or a partial match<br> - the title of the page<br> - the iteration number. Because the GCV API puts a limit on its output, we had to reupload the identified images to the API to extend our search. We continued these iterations until no more new unique URLs were found<br> - the language found by the ``langid`` Python module [link](https://github.com/saffsd/langid.py), along with the normalized score.<br> - the labels associated with the image by Google<br> - the scrape date</p> <p>Alongside the .tsv-files, there are several other elements in the following folder structure:</p> <p>```<br> ├── data<br> │ ├── embeddings<br> │ └── doc2vec<br> │ └── input-text<br> │ └── metadata<br> │ └── umap<br> │ └── evaluation<br> │ └── results<br> │ └── diachronic-plots<br> │ └── top-words<br> │ └── tsv<br> ```</p> <p>1. The ```/embeddings``` folder contains the doc2vec models, the training input for the models, the metadata (id, URL, date) and the UMAP embeddings used in the GMM clustering. Please note that the date parser was not able to find dates for all webpages and for this reason not all training texts have associated metadata.<br> 2. The ```/evaluation``` folder contains the AIC and BIC scores for GMM clustering with different numbers of clusters.<br> 3. The ```/results``` folder contains the top words associated with the clusters and the diachronic cluster prominence plots.</p> <p>## Data Cleaning and Curation<br> Our pipeline contained several interventions to prevent noise in the data. First, in between the iterations we manually checked the scraped photos for relevance. We did so because reuploading an iconic image that is paired with another, irrelevant, one results in reproductions of the irrelevant one in the next iteration. Because we did not catch all noise, we used Scale Invariant Feature Transform (SIFT), a basic computer vision algorithm, to remove images that did not meet a threshold of ten keypoints. By doing so we removed completely unrelated photographs, but left room for variations of the original (such as painted versions of Che Guevara, or cropped versions of the Napalm Girl image). Another issue was the parsing of webpage texts. After experimenting with different webpage parsers that aim to extract 'relevant' text it proved too difficult to use one solution for all our webpages. Therefore we simply parsed all the text contained in commonly used html-tags, such as ```<p>```, ```<h1>``` etc.</p>
Dataset related to the article "Clinical and Molecular Data Define a Diagnosis of Arrhythmogenic Cardiomyopathy in a Carrier of a Brugada-Syndrome-Associated PKP2 Mutation"
<p>This record contains raw data related to the article “ Molecular Data Define a Diagnosis of Arrhythmogenic Cardiomyopathy in a Carrier of a Brugada-Syndrome-Associated PKP2 Mutation”. </p> <p>Plakophilin-2 (<em>PKP2</em>) is the most frequently mutated desmosomal gene in arrhythmogenic cardiomyopathy (ACM), a disease characterized by structural and electrical alterations predominantly affecting the right ventricular myocardium. Notably, ACM cases without overt structural alterations are frequently reported, mainly in the early phases of the disease. Recently, the <em>PKP2</em> p.S183N mutation was found in a patient affected by Brugada syndrome (BS), an inherited arrhythmic channelopathy most commonly caused by sodium channel gene mutations. We here describe a case of a patient carrier of the same BS-related <em>PKP2</em> p.S183N mutation but with a clear diagnosis of ACM. Specifically, we report how clinical and molecular investigations can be integrated for diagnostic purposes, distinguishing between ACM and BS, which are increasingly recognized as syndromes with clinical and genetic overlaps. This observation is fundamentally relevant in redefining the role of genetics in the approach to the arrhythmic patient, progressing beyond the concept of "one mutation, one disease", and raising concerns about the most appropriate approach to patients affected by structural/electrical cardiomyopathy. The merging of genetics, electroanatomical mapping, and tissue and cell characterization summarized in our patient seems to be the most complete diagnostic algorithm, favoring a reliable diagnosis.</p>
Data archive for the peer-reviewed journal article "Variability in the mass absorption cross-section of black carbon (BC) aerosols is driven by BC internal mixing state at a central European background site (Melpitz, Germany) in winter""
<p>Data archive for figures accompanying the peer-reviewed journal article "Variability in the mass absorption cross-section of black carbon (BC) aerosols is driven by BC internal mixing state at a central European background site (Melpitz, Germany) in winter". In 2020 this article was accepted for publication in the journal <em>Atmospheric Chemistry and Physics</em>. Data are uploaded in the form of Igor Pro experiment files (.pxp).</p>
data for article "Enhancement of Superconductivity by Amorphizing Molybdenum Silicide Films Using a Focused Ion Beam"
<p>This dataset is the compilation of data used in the article "Enhancement of Superconductivity by Amorphizing Molybdenum Silicide Films Using a Focused Ion Beam" (<a href="https://doi.org/10.3390/nano10050950">https://doi.org/10.3390/nano10050950</a>). For more info of samples see metadata2.txt</p>
Data for the article: "Molecular Modelling Reveals Eight Novel Druggable Binding Sites in SARS-CoV-2's Spike Protein" by Ilke Ugur and Antoine Marion
<p>This upload contains data related to the article<br> published as a preprint on ChemRxiv with DOI<br> https://doi.org/10.26434/chemrxiv.13292768</p> <p>"Molecular Modelling Reveals Eight Novel Druggable Binding Sites in SARS-CoV-2's Spike Protein"<br> by Ilke Ugur and Antoine Marion (2020)<br> Department of Chemistry, Middle East Technical University, Ankara, Turkey.</p> <p>For further information, please contact:<br> ilkeugur@metu.edu.tr ; amarion@metu.edu.tr</p> <p>The manuscript is currently under peer-review.</p> <p>Content:</p> <p>Library of molecules derived from DrugBank v 5.1.5:<br> - DrugBank_2020_5.1.5/ # All necessary files for the docking and refinement of the library of molecules.<br> -- DB_5.1.5_pH7.4_pdbqt/ ## PDBQT readily usable for docking with AutoDock Vina.<br> -- DB_5.1.5_pH7.4_mol2amber/ ## mol2 files containing assigned GAFF atom types and Gasteiger atomic charges.<br> -- DB_5.1.5_pH7.4_frcmod/ ## frcmod files containing missing molecular mechanics parameters<br> -- dbID_name.dat ## DrugBank ID to generic name dictionary</p> <p>Note: The files were prepared automatically via a series of operations handling openbabel and antechamber.<br> The protonation state of ionizable groups as well as Gasteiger atomic charges were assigned by openbabel for a pH of 7.4<br> mol2 and frcmod files can be used readily via the tleap module of AmberTools to produce topology files.</p> <p><br> Receptor structures:<br> - receptors/ # PDB files for the four structures of the spike protein considered in this work<br> -- CS00ns.pdb ## Closed state after the remodelling of missing loops (PDB ID 6vxx)<br> -- OS00ns.pdb ## Open state after the remodelling of missing loops (PDB ID 6vyb)<br> -- CS25ns.pdb ## Closed state after 25 ns of molecular dynamics in explicit water<br> -- OS25ns.pdb ## Open state after 25 ns of molecular dynamics in explicit water</p> <p>Note: All structures are aligned to CS00ns.pdb and can be converted to pdbqt for docking with AutoDock Vina</p> <p><br> Docking grid centers:<br> - dockingCenters/ # XYZ files containing the coordinates of each docking grid center considered in this work</p> <p>Note: The coordinates are given in the same frame as that of the four structures of the receptor.</p> <p><br> Binding sites:<br> - bindingSites/ # XYZ files with the coordinates of the representative atomic centres<br> # of each binding site identified in this work (A-H).</p> <p>Note: These files can be used to get a clearer picture of the binding sites within the structures<br> of the spike protein shared in the receptors directory.</p> <p><br> Final modelling results:<br> - allData.txt # data for all molecules in the set (approved and investigational)<br> - appData.txt # data for approved molecules only<br> - data.xlsx # data for all molecules in the set (approved and investigational)<br> # as a formatted excel spreadsheet</p> <p>Note: The columns are delimited with semi-colons ";".<br> The files contain the results for the best pose of all approved molecules for which<br> molecular mechanics-based geometry optimization succeeded, regardless of their score.<br> For other molecules, the result of their best pose is reported only for those complexes<br> having MM interaction energy lower or equal to -22.00 kcal/mol.</p> <p><br> Visualization:<br> - bs.pse # pymol session representing the binding sites within the<br> # closed state structure of the spike protein (CS00ns)<br> - pt.pse # pymol session representing the docking grid centres within<br> # closed statestructure of the spike protein (CS00ns)</p> <p>Note: the PSE files should be compatible with version 7.0 of pymol and later</p>
Data set for the article "Efficient Computation of the Magnetic Polarizability Tensor Spectral Signature using POD"
<p>Data set to accompany the article "Efficient Computation of the Magnetic Polarizability Tensor Spectral Signature using POD" written by B.A. Wilson (Swansea University) and P.D. Ledger (Keele University)</p>
Dataset related to article "The soluble glycoprotein NMB (GPNMB) produced by macrophages induces cancer stemness and metastasis via CD44 and IL-33"
<p>This record contains data related to article “The soluble glycoprotein NMB (GPNMB) produced by macrophages induces cancer stemness and metastasis via CD44 and IL-33"</p> <p> </p> <p>Abstract</p> <p>In cancer, myeloid cells have tumor-supporting roles. We reported that the protein GPNMB (glycoprotein nonmetastatic B) was profoundly upregulated in macrophages interacting with tumor cells. Here, using mouse tumor models, we show that macrophage-derived soluble GPNMB increases tumor growth and metastasis in Gpnmb-mutant mice (DBA/2J). GPNMB triggers in the cancer cells the formation of self-renewing spheroids, which are characterized by the expression of cancer stem cell markers, prolonged cell survival and increased tumor-forming ability. Through the CD44 receptor, GPNMB mechanistically activates tumor cells to express the cytokine IL-33 and its receptor IL-1R1L. We also determined that recombinant IL-33 binding to IL-1R1L is sufficient to induce tumor spheroid formation with features of cancer stem cells. Overall, our results reveal a new paracrine axis, GPNMB and IL-33, which is activated during the cross talk of macrophages with tumor cells and eventually promotes cancer cell survival, the expansion of cancer stem cells and the acquisition of a metastatic phenotype.</p> <p> </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.