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2,394
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ShareScore release 0.9.0
Dataset results
2,394 results for “ms”
MicroRNA regulate immune pathways in T-cells in multiple sclerosis (MS)
GEO Series GSE43592. synthetic construct; Homo sapiens. 40 samples. Type: Expression profiling by array; Non-coding RNA profiling by array.
Comparison of the expression profiles of the 630E JIR8094 strain and sporulation sigma factor mutants (sigE, sigF, sigG, sigK, spoIIID) in MS
GEO Series GSE43202. Clostridioides difficile. 18 samples. Type: Expression profiling by array.
longitudinal expression profiling in whole blood of multiple sclerosis patients and controls [MS vs Ctrl Discovery dataset]
GEO Series GSE41848. Homo sapiens. 212 samples. Type: Expression profiling by array.
Transcriptomic profiling of blood mTreg and mTeff from healthy control (HC) and multiple sclerosis (MS)
GEO Series GSE274001. Homo sapiens. 154 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Changes in adaptive immunity and increased neuroinflammation are key processes in ageing EAE: a road to develop new therapeutic strategies for elderly MS patients
GEO Series GSE227650. Mus musculus. 40 samples. Type: Expression profiling by high throughput sequencing.
longitudinal expression profiling in whole blood of multiple sclerosis patients and controls [MS vs Ctrl Replication dataset]
GEO Series GSE41849. Homo sapiens. 102 samples. Type: Expression profiling by array.
Gene expression data from WM983B melanoma cells treated with vehicle or 2.5 µM inhibitor (corin2 or MS-275) for 24 h
GEO Series GSE87289. Homo sapiens. 9 samples. Type: Expression profiling by array.
Gene expression data: Plasmacytoid dendritic cells (pDCs) of healthy donors and MS patientes before and after IFN beta treatment
GEO Series GSE37750. Homo sapiens. 26 samples. Type: Expression profiling by array.
PROTEOFORMER: deep proteome coverage through ribosome profiling and MS integration
GEO Series GSE58207. Homo sapiens. 2 samples. Type: Expression profiling by high throughput sequencing.
Expression data from human whole blood of propionate treated MS patients
GEO Series GSE116835. Homo sapiens. 8 samples. Type: Expression profiling by array.
FoxA1 directs the lineage and immunosuppressive properties of FoxA1+ regulatory T cells in EAE and MS
GEO Series GSE54490. Mus musculus. 12 samples. Type: Expression profiling by array.
Catchet-MS identifies IKZF1-targeting Thalidomide analogues as novel HIV-1 latency reversal agents
GEO Series GSE196059. Homo sapiens. 2 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
tissue exposed to (I) no primary, (]) antibodies to avian collagen I, or (K) collagenase digestion followed by antibodies to avian collagen I, as described {11). Data in (I), (J), and (K) were collected at 149-ms integration. in Analyses of Soft Tissue from Tyrannosaurus rex Suggest the Presence of Protein
tissue exposed to (I) no primary, (]) antibodies to avian collagen I, or (K) collagenase digestion followed by antibodies to avian collagen I, as described {11). Data in (I), (J), and (K) were collected at 149-ms integration.
Study on electron stochastic motions in the MS wave field: Test particle simulations
<p>The data used to generate the figures in this study.</p>
Imaging MS data of Ciona brain No. 1
<p>Imaging MS data of the Ciona brain. 10 um sections. Apparatus: Bruker rapifleX.</p>
BRAINTEASER ALS and MS Datasets
<p><a href="https://brainteaser.health/">BRAINTEASER</a> (Bringing Artificial Intelligence home for a better care of amyotrophic lateral sclerosis and multiple sclerosis) is a data science project that seeks to exploit the value of big data, including those related to health, lifestyle habits, and environment, to support patients with <em>Amyotrophic Lateral Sclerosis (ALS)</em> and <em>Multiple Sclerosis (MS)</em> and their clinicians. Taking advantage of cost-efficient sensors and apps, BRAINTEASER will integrate large, clinical datasets that host both patient-generated and environmental data.</p> <p>As part of its activities, BRAINTEASER organized three open evaluation challenges on <em>Intelligent Disease Progression Prediction (iDPP)</em>, <a href="https://brainteaser.health/open-evaluation-challenges/idpp-2022/">iDPP@CLEF 2022,</a> <a href="https://brainteaser.health/open-evaluation-challenges/idpp-2023/">iDPP@CLEF 2023</a>, and <a href="https://brainteaser.health/open-evaluation-challenges/idpp-2024/">iDPP@CLEF 2024</a> co-located with the <a href="https://www.clef-initiative.eu/">Conference and Labs of the Evaluation Forum (CLEF)</a>.</p> <p>The goal of iDPP@CLEF is to design and develop an evaluation infrastructure for AI algorithms able to:</p> <ul> <li>better describe <strong>disease mechanisms</strong>;</li> <li><strong>stratify patients</strong> according to their phenotype assessed all over the disease evolution;</li> <li><strong>predict disease progression</strong> in a probabilistic, time-dependent fashion.</li> </ul> <p>The iDPP@CLEF challenges relied on retrospective and prospective ALS and MS patient data made available by the clinical partners of the BRAINTEASER consortium.</p> <h2>Retrospective Dataset</h2> <p>We release three retrospective datasets, one for ALS and two for MS. The two retrospective MS datasets, one consisting of clinical data only and one with clinical data and environmental/pollution data.</p> <p>The retrospective datasets contain data about <strong>2,204 ALS patients</strong> (static variables, ALSFRS-R questionnaires, spirometry tests, environmental/pollution data) and <strong>1,792 MS patients</strong> (static variables, EDSS scores, evoked potentials, relapses, MRIs). A subset of <strong>280 MS patients</strong> contains environmental and pollution data.</p> <p>More in detail, the BRAINTEASER project <em>retrospective datasets</em> were derived from the merging of already existing datasets obtained by the clinical centers involved in the BRAINTEASER Project. </p> <ul> <li>The ALS dataset was obtained by the merge and homogenisation of the Piemonte and Valle d’Aosta Registry for Amyotrophic Lateral Sclerosis (PARALS, Chiò et al., 2017) and the Lisbon ALS clinic (CENTRO ACADÉMICO DE MEDICINA DE LISBOA, Centro Hospitalar Universitário de Lisboa-Norte, Hospital de Santa Maria, Lisbon, Portugal,) dataset. Both datasets were initiated in 1995 and are currently maintained by researchers of the ALS Regional Expert Centre (CRESLA), University of Turin, and of the CENTRO ACADÉMICO DE MEDICINA DE LISBOA-Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa. They include demographic and clinical data, comprehending both static and dynamic variables.</li> <li>The MS dataset was obtained from the Pavia MS clinical dataset, which was started in 1990 and contains demographic and clinical information that is continuously updated by the researchers of the Institute and the Turin MS clinic dataset (Department of Neurosciences and Mental Health, Neurology Unit 1, Città della Salute e della Scienza di Torino.</li> <li>Retrospective environmental data are accessible at various scales at the individual subject level. Thus, environmental data have been retrieved at different scales: <ul> <li>To gather macroscale air pollution data we’ve leveraged data coming from public monitoring stations that cover the whole extension of the involved countries, namely the <a href="https://aqportal.discomap.eea.europa.eu/">European Air Quality Portal</a>;</li> <li> data from a network of air quality sensors (PurpleAir - Outdoor Air Quality Monitor / PurpleAir PA-II) installed in different points of the city of Pavia (Italy) were extracted as well. In both cases, environmental data were previously publicly available. In order to merge environmental data with individual subject locations we leverage postcodes (postcodes of the station for the pollutant detection and postcodes of subject address). Data were merged following an anonymization procedure based on hash keys. Environmental exposure trajectories have been pre-processed and aggregated in order to avoid fine temporal and spatial granularities. Thus, individual exposure information could not disclose personal addresses.</li> </ul> </li> </ul> <p>The retrospective datasets are shared in two formats:</p> <ul> <li>RDF (serialized in Turtle) modeled according to the <a href="https://doi.org/10.5281/zenodo.12789731">BRAINTEASER Ontology (BTO)</a>;</li> <li>CSV, as shared during the iDPP@CLEF 2022 and 2023 challenges, split into training and test.</li> </ul> <p>Each format corresponds to a specific folder in the datasets, where a dedicated README file provides further details on the datasets. Note that the ALS dataset is split into multiple ZIP files due to the size of the environmental data.</p> <h2>Prospective Dataset</h2> <p>For the iDPP@CLEF 2024 challenge, the datasets contain prospective data about <strong>86 ALS patients</strong> (static variables, ALSFRS-R questionnaires compiled by clinicians or patients using the BRAINTEASER mobile application, sensors data).</p> <p>The prospective datasets are shared in two formats:</p> <ul> <li>RDF (serialized in Turtle) modeled according to the <a href="https://doi.org/10.5281/zenodo.12789731">BRAINTEASER Ontology (BTO)</a>;</li> <li>CSV, as shared during the iDPP@CLEF 2024 challenge, split into training and test.</li> </ul> <p>Each format corresponds to a specific folder in the datasets, where a dedicated README file provides further details on the datasets. Note that the MS dataset is split into multiple ZIP files due to the size of the environmental data.</p> <p>The <strong>BRAINTEASER Data Sharing Policy</strong> section below reports the details for requesting access to the datasets.</p>
HR. MS. TROMP IN NEDERLAND TERUG
<u>Source</u>: Europeana <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1652249801.2213.jpg">https://4dcity.org/imgupload/1652249801.2213.jpg</a> <br><u>Original Image URL</u>: <a href="https://api.europeana.eu/thumbnail/v2/url.json?uri=https%3A%2F%2Fwww.openbeelden.nl%2Fimages%2F1212317%2FHR._MS._TROMP_IN_NEDERLAND_TERUG_%25280_26%2529.png&type=VIDEO">https://api.europeana.eu/thumbnail/v2/url.json?uri=https%3A%2F%2Fwww.openbeelden.nl%2Fimages%2F1212317%2FHR._MS._TROMP_IN_NEDERLAND_TERUG_%25280_26%2529.png&type=VIDEO</a> <br><br><u>Image-Metadata:</u><br>Filename: 1652249801.2213.jpg<br>Image Dimensions: 360x288<br>Megapixels: 0.10 MP<br>Filesize: 89.38 KB<br>
HET PLAATSEN VAN DE SCHOORSTEEN OP HET MS "ORANJE"
<u>Source</u>: Europeana <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1652249783.9182.jpg">https://4dcity.org/imgupload/1652249783.9182.jpg</a> <br><u>Original Image URL</u>: <a href="https://api.europeana.eu/thumbnail/v2/url.json?uri=https%3A%2F%2Fwww.openbeelden.nl%2Fimages%2F1211991%2FHET_PLAATSEN_VAN_DE_SCHOORSTEEN_OP_HET_MS_quot_ORANJE_quot_%25280_34%2529.png&type=VIDEO">https://api.europeana.eu/thumbnail/v2/url.json?uri=https%3A%2F%2Fwww.openbeelden.nl%2Fimages%2F1211991%2FHET_PLAATSEN_VAN_DE_SCHOORSTEEN_OP_HET_MS_quot_ORANJE_quot_%25280_34%2529.png&type=VIDEO</a> <br><br><u>Image-Metadata:</u><br>Filename: 1652249783.9182.jpg<br>Image Dimensions: 360x288<br>Megapixels: 0.10 MP<br>Filesize: 94.41 KB<br>
DE JANTJES VAN HR MS "TROMP" MARCHEREN
<u>Source</u>: Europeana <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1652249781.23.jpg">https://4dcity.org/imgupload/1652249781.23.jpg</a> <br><u>Original Image URL</u>: <a href="https://api.europeana.eu/thumbnail/v2/url.json?uri=https%3A%2F%2Fwww.openbeelden.nl%2Fimages%2F1210859%2FDE_JANTJES_VAN_HR_MS_quot_TROMP_quot_MARCHEREN_%25280_17%2529.png&type=VIDEO">https://api.europeana.eu/thumbnail/v2/url.json?uri=https%3A%2F%2Fwww.openbeelden.nl%2Fimages%2F1210859%2FDE_JANTJES_VAN_HR_MS_quot_TROMP_quot_MARCHEREN_%25280_17%2529.png&type=VIDEO</a> <br><br><u>Image-Metadata:</u><br>Filename: 1652249781.23.jpg<br>Image Dimensions: 360x288<br>Megapixels: 0.10 MP<br>Filesize: 110.23 KB<br>
TEWATERLATING VAN HET MS "ALBIREO"
<u>Source</u>: Europeana <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1652249777.484.jpg">https://4dcity.org/imgupload/1652249777.484.jpg</a> <br><u>Original Image URL</u>: <a href="https://api.europeana.eu/thumbnail/v2/url.json?uri=https%3A%2F%2Fwww.openbeelden.nl%2Fimages%2F1190075%2FTEWATERLATING_VAN_HET_MS_quot_ALBIREO_quot_%25280_19%2529.png&type=VIDEO">https://api.europeana.eu/thumbnail/v2/url.json?uri=https%3A%2F%2Fwww.openbeelden.nl%2Fimages%2F1190075%2FTEWATERLATING_VAN_HET_MS_quot_ALBIREO_quot_%25280_19%2529.png&type=VIDEO</a> <br><br><u>Image-Metadata:</u><br>Filename: 1652249777.484.jpg<br>Image Dimensions: 360x288<br>Megapixels: 0.10 MP<br>Filesize: 96.12 KB<br>
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.