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126,115 results for “Patients”
Dataset Multifaceted intervention for patients admitted to an emergency unit for suicide attempt: an exploratory study
<p>This dataset is related to "Multifaceted intervention for patients admitted to an emergency unit for suicide attempt: an exploratory study" (Brovelli S., Dorogi Y., Feiner A.-S., Golay P., Stiefel F., Bonsack C. & Michaud L.)</p>
MelanoDB: Dataset files of clinical and molecular features of advanced melanoma patients treated with MAPK inhibitors
<p>MAPK inhibitors have significantly improved overall survival in patients with metastatic melanoma disease but their efficacy is still limited by primary or acquired resistance. Several studies have attempted to predict response to MAPK inhibitor therapy, however the lack of a consistent cohort prevents better definition of associations between treatment efficacy and clinical and/or molecular features. Here, we present MelanoDB, a collection of patients with metastatic melanoma treated with MAPK inhibitors. We formatted data from 8 different studies for a total of 417 cases to gather common clinical and molecular features. Whole or partial exome sequencing is available for 191 cases and gene expression for 132 cases. We provide a web application to explore the integrated data and its distribution among the collected studies, and we share this dataset to the scientific community according to FAIR principles</p> <p>These data are available under the licence CC-BY-SA.</p> <p>Here we provide a web application viewer of the database content: http://melanodb-ircm.montp.inserm.fr/</p> <p>You are requested to cite this repository in the case of using these data in a publication.</p>
A Systematic Review and Meta-Analysis of Mindfulness-Based (Baduanjin) Exercise for the Rehabilitation of Stroke Patients
<p><span>A Systematic Review and Meta-Analysis of Mindfulness-Based (Baduanjin) Exercise for the Rehabilitation of Stroke Patients</span></p>
Data inputs and results from AI-supported title and abstract screening "Lack of evidence regarding markers identifying acute heart failure in patients with COPD: an AI-supported systematic review"
<p>These comma-separated data files were used to conduct the AI supported screening of [Lack of Evidence Regarding Markers Identifying Acute Heart Failure in Patients with COPD: An AI-supported Systematic Review (working title)], following the methodology described in the publication (URL/doi to be uploaded).</p> <p>These files provide insight into the AI-supported screening process and the choices made by the human reviewer.</p>
Neither alpha-synuclein-preformed fibrils derived from patients with GBA1 mutations nor the host murine genotype significantly influence seeding efficacy in the mouse olfactory bulb
<p>Data sets for;</p> <p>Neither alpha-synuclein-preformed fibrils derived from patients with <em>GBA1</em> mutations nor the host murine genotype significantly influence seeding efficacy in the mouse olfactory bulb</p>
Repository of Thoracolumbar Osteo-Ligamentous Spine Patient-Personalised FE Meshes
<p><em><strong>Repository of Thoracolumbar Osteo-Ligamentous Spine Patient-Personalised FE Meshes:</strong></em></p> <ul> <li>42 FE input files (.inp extension, Abaqus software, Simulia) representing patient-personalised thoracolumbar spine hexahedral meshes, including point coordinates, mesh connectivity IDs and element sets. Each input file is almost 99MB (totally 3.86GB), and it includes vertebras and IVDs hexahedral meshes; pelvis, sacrum, and the femoral head triangulated meshes; and ligaments.</li> <li>An excel file: "<a href="../records/10994164/files/Descriptive_List%20(42_P-S_FE_Models).xlsx?download=1">Descriptive_List (42_P-S_FE_Models).xlsx</a>" reporting measured spinopelvic parameters for 42 patient-personalised FE hexahedral meshes. The Excel file includes measured spinopelvic parameters (PI, PT, SS, LL, LL-PI, GT, RPV, RLL, LDI, RSA, TPA, and scoliosis cobb angle), GAP and IVD centric thickness for FE virtual cohort and patient-personalised FE meshes. Model ID in the excel file is correspondent to the model’s name.</li> <li>One png file: "<a href="../records/10994164/files/42_P-S.png?download=1">42_P-S.png</a>" representing the first 10 patient-personalised thoracolumbar spine hexahedral models out of 42 FE models.</li> </ul> <p><em><strong>Notes:</strong></em></p> <p>1- Model number in "<a href="../records/10994164/files/Descriptive_List%20(42_P-S_FE_Models).xlsx?download=1">Descriptive_List (42_P-S_FE_Models).xlsx</a>" is correspondent to the same model number in the 42 stereolithography (stl) files (.stl extension) representing the thoracolumbar spine triangulated meshes (DOI: <a href="https://doi.org/10.5281/zenodo.8108354">10.5281/zenodo.8108354</a>; <a href="../records/8108354/files/42%20Patient-Specific%20stl%20files.rar?download=1">42 Patient-Specific stl files.rar</a>).</p> <p>2-Models are reconstructed thanks to the Statistical Shape Modelling (SSM) and mesh morphing techniques, i.e., spine sagittal geometrical parameters could be measured by a clinical software like sterEOS or Surgimap, then, different shape modes of morphed-mesh SSM tool could be activated in order to obtain spine deformity. Then, pros and cons analyses between patient geometrical data and synthesized geometrical information could exploit FE patient-personalised thoracolumbar osteo-ligamentous spine models.</p> <p>3- FE inp files can be opened by Abaqus 2019 and later. Any other FE software which supports .inp extension also can open the files.</p> <p><em><strong>Developed by: </strong></em>Morteza Rasouligandomani (Ph.D. in biomedical engineering, Pompeu Fabra university, BCN Med-Tech group, DTIC department, Barcelona, Spain).</p> <p>Email contact: jerome.noailly@upf.edu</p>
Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitor therapy reduces the level of DNA damage in patients with heterozygous familial hypercholesterolemia
<p><span><span>Heterozygous Familial Hypercholesterolaemia (HeFH) is a common autosomal dominant genetic disease (1:300) characterized by elevated LDL-C leading to premature atherosclerosis. Treatment with a PCSK9 inhibitor (iPCSK9) is recommended in high cardiovascular risk FH patients if the treatment goal is not achieved on maximal tolerated statin plus ezetimibe. </span></span><span>The aim of this study was to </span><span><span>examine the changes in DNA damage in HeFH patients associated with iPCSK9 use. </span></span><span>Fifty-seven patients were included: a normolipidemic group (control; n=20) and patients with HeFH (study group; n=36). DNA damage was determined by alkaline comet assay. PCSK9 protein level was assessed by ELISA. </span><span>The levels of Lp(a) in human serum were quantitatively turbidimetrically assay.</span><span> </span><span>PCSK9i treatment was associated with lower DNA damage, Lp(a), PCSK9 and lipid profile than before treatment. However, 20 of 36 patients still had Lp(a) values above 125 nmol/L, and reduced Lp(a) did not correlate with reduced DNA damage. Reduced PCSK9 moderately (r=0.48) correlates with reduced DNA damage</span><span><span>. PCSK9i therapy reduces the level of DNA damage in HeFH patients, regardless of the type of inhibitor. The reduction in DNA damage is not related to the changes in lipid profile or Lp(a) induced by PCSK9i, but it is dependent on PCSK9 level.</span></span></p>
Catalog of stool metagenome-assembled genomes from patients with different cancer types
<p><strong>A non-redundant catalog of 3,816 genomes with at least 75% completeness and no more than 15% contamination assembled from metagenomes. Samples of 976 metagenomes were obtained from patients receiving immunotherapy for the treatment of different types of cancers.</strong></p>
Cell-free DNA Fragmentomics and Second Malignant Neoplasm Risk in Patients with PTEN Hamartoma Tumor Syndrome
<p><strong>Supplementary dataset for manuscript:</strong></p> <p><strong>Cell-free DNA Fragmentomics and Second Malignant Neoplasm Risk in Patients with PTEN Hamartoma Tumor Syndrome</strong></p> <p>Affiliations:</p> <p><sup>1</sup>Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA</p> <p><sup>2</sup>Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH 44195, USA</p> <p><sup>3</sup>Rose Ella Burkhardt Brain Tumor and Neuro-Oncology Center, Cleveland Clinic, Cleveland, OH 44195, USA</p> <p><sup>4</sup>Center for Personalized Genetic Healthcare, Medical Specialties Institute, Cleveland Clinic, Cleveland, OH 44195, USA</p> <p><sup>5</sup>Center for Immunotherapy and Precision Immuno-oncology, Cleveland Clinic, Cleveland, OH 44195, USA</p> <p><sup>6</sup>Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH 44195, USA</p> <p><sup>7</sup>Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA</p> <p><sup>8</sup>Germline High Risk Cancer Focus Group, Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH 44106, USA</p> <p><strong><em>Correspondence</em></strong>:</p> <p>Darren Liu, MD, MS (<a href="https://orcid.org/0000-0002-6703-1843">https://orcid.org/0000-0002-3693-5145)</a></p> <p>Cleveland Clinic Genomic Medicine Institute</p> <p>9500 Euclid Avenue, Cleveland, OH 44195, USA</p> <p>E-mail: liud5@ccf.org </p>
Phase I trial of CX-5461, a first-in-class G-quadruplex stabilizer in patients with advanced solid tumors enriched for DNA-repair deficiencies (CCTG IND.231) - Variant Calls
<p>Variant Calls from Phase I trial of CX-5461, a first-in-class G-quadruplex stabilizer in patients with advanced solid tumors enriched for DNA-repair deficiencies (CCTG IND.231)</p> <p>See publication for methodology.</p>
Dysglycemias in patients admitted to ICUs with severe acute respiratory syndrome due to COVID-19 versus other causes – A cohort study - Dataset
<p>Dataset of a cohort whose summary is described below.</p> <p>Abstract</p> <p>Importance: Dysglycemias have been associated with worse prognosis in critically ill patients with or without diabetes, but data on their association with severe COVID-19 and outcomes are lacking. Objectives: To analyze the relationship of dysglycemias with COVID-19 in hospitalized patients with severe acute respiratory syndrome (SARS) and assess the influence of dysglycemias on mortality. Design, Setting and Participants: Cohort of consecutive patients with SARS and suspected COVID-19 hospitalized in intensive care units (ICUs) across eight hospitals in Curitiba-Brazil. Main Outcomes and Measures: The primary outcome was the influence of COVID-19 on the variation of the following parameters of dysglycemia: highest glucose level at admission, mean and highest glucose levels during ICU stay, mean glucose variation, and percentage of days with hyperglycemia. The secondary outcome was the influence of COVID-19 and each of the five parameters of dysglycemia on hospital mortality within 30 days from ICU admission. Results: We compared 703 patients with COVID-19 and 138 without COVID-19 admitted to the ICUs due to SARS. Compared with patients without COVID-19, those with COVID-19 had significantly higher glucose peaks at admission (198.1mg/dL vs. 167.8mg/dL, respectively) and during ICU stay (285.9mg/Dl vs. 230.9md/dL), higher mean daily glucose values (167.9mg/dL vs. 149.8mg/dL), higher percentage of days with hyperglycemia during ICU stay (vs. 45.0 vs. 31.5), and greater mean daily glucose variations (85.3mg/dL vs. 63.5mg/dL). However, these associations were lost after adjustment for APACHE II scores, SOFA scores, CRP level, corticosteroid use and nosocomial infection. Dysglycemia and COVID-19 were each independent risk factors for mortality. Conclusions and Relevance: Patients with SARS due to COVID-19 had higher mortality and more frequent dysglycemia than patients with SARS due to other causes. This association seemed to be related to disease severity and inflammation and was independent of corticosteroid use, suggesting no specific relationship with the SARS-CoV-2 infection.</p>
Longitudinal characterization of circulating neutrophils uncovers distinct phenotypes associated with severity in hospitalized COVID-19 patients
<p>Code and data for the manuscript "Longitudinal characterization of circulating neutrophils uncovers distinct phenotypes associated with severity in hospitalized COVID-19 patients".</p> <p>Contains all code located at <a href="https://github.com/lasalletj/COVID_Neutrophils">https://github.com/lasalletj/COVID_Neutrophils</a> as well as additional data files needed to run the code.</p> <p>Three additional publicly available data objects are required to run the code from start to finish. The first, covid.combined_final.Robj, from the Sinha et al. Nature Medicine 2022 paper (<a href="https://doi.org/10.1038/s41591-021-01576-3">https://doi.org/10.1038/s41591-021-01576-3</a>), is downloadable from the following link: <a href="https://figshare.com/ndownloader/files/31562957">https://figshare.com/ndownloader/files/31562957</a>. The other two required objects, seurat_COVID19_Neutrophils_cohort2_rhapsody_jonas_FG_2020-08-18.rds and seurat_COVID19_freshWB-PBMC_cohort2_rhapsody_jonas_FG_2020-08-18.rds, are from the Schulte-Schrepping et al. Cell 2020 paper (<a href="https://doi.org/10.1016/j.cell.2020.08.001">https://doi.org/10.1016/j.cell.2020.08.001</a>), and can be downloaded from <a href="https://beta.fastgenomics.org/datasets/detail-dataset-ee4b1a0f339140ad82f861aea35076f1#Files">https://beta.fastgenomics.org/datasets/detail-dataset-ee4b1a0f339140ad82f861aea35076f1#Files</a> and <a href="https://beta.fastgenomics.org/datasets/detail-dataset-1ad2967be372494a9fdba621610ad3f3#Files">https://beta.fastgenomics.org/datasets/detail-dataset-1ad2967be372494a9fdba621610ad3f3#Files</a>, respectively.</p> <p>Any additional information required to reanalyze the data reported in this work paper is available from the Lead Contact, Moshe Sade-Feldman (msade-feldman@mgh.harvard.edu) upon request.</p>
GERDAT011 Literature search for publication - Geriatric assessment in the management of older patients with cancer – a systematic review (update).xlsx
<p>Search data belonging to the publication Geriatric assessment in the management of older patients with cancer – a systematic review (update)</p>
GERDAT010 Dataset for literature search linked to publication "Information needs of older patients newly diagnosed with cancer"
<p>Dataset of the literature search belonging to the publication "Information needs of older patients newly diagnosed with cancer"</p>
TCRb sequencing of CD4+ and CD8+ T cells from hematological patients (part 1)
<p>This dataset contains TCRb sequencing of 177 samples from patients with aplastic anemia, myelodysplastic syndrome, immune thrombocytopenia, immunodeficiency or graft-versus-host disease and healthy controls. Samples are separated CD4+ or CD8+ cells from peripheral blood or bone marrow. The data has been produced with immunoSEQ platform (Adaptive Biotechnologies). The details regarding sample processing, sequencing and metadata can be found from the publication <em>Somatic mutations associate with clonal expansion of CD8+ T cells</em> (Lundgren et al, Science Advances, in press).</p> <p>The dataset is divided in 2 parts containing 91 (part 1) and 86 (part 2) files. Data is in immunoSEQ format (v2).</p>
Functional Near-Infrared Spectroscopy Reveals Delayed Hemodynamic Changes in the Primary Motor Cortex During Fine Motor Tasks and Decreased Interhemispheric Connectivity in Parkinson's Disease Patients
<p>This dataset contains functional near-infrared spectroscopy (fNIRS) data from 20 patients with Parkinson’s disease and 20 age- and sex-matched healthy subjects without movement disorders. There are 3 folders, each corresponding to a different task: a 10-second finger-tapping task, a 2-minute walking task, and a 6-minute resting-state. When using this dataset, please cite our work:</p> <div> <div>Guevara, E., Rivas-Ruvalcaba, F. J., Kolosovas-Machuca, E. S., Ramírez-Elías, M., Zapata, R. D. de L., Ramirez-GarciaLuna, J. L., & Rodríguez-Leyva, I. (2024). Parkinson’s disease patients show delayed hemodynamic changes in primary motor cortex in fine motor tasks and decreased resting-state interhemispheric functional connectivity: A functional near-infrared spectroscopy study. <em>Neurophotonics</em>, <em>11</em>(2), 025004. <a href="https://doi.org/10.1117/1.NPh.11.2.025004">https://doi.org/10.1117/1.NPh.11.2.025004</a></div> <div> <div> <div>Guevara, E., Solana-Lavalle, G., & Rosas-Romero, R. (2024). Integrating fNIRS and machine learning: Shedding light on Parkinson’s disease detection. <em>EXCLI Journal</em>, <em>23</em>, 763–771. <a href="https://doi.org/10.17179/excli2024-7151">https://doi.org/10.17179/excli2024-7151</a></div> <div> <div> <div> <div> <div>Guevara, E., Kolosovas-Machuca, E. S., & Rodríguez-Leyva, I. (2024). Exploring motor cortex functional connectivity in Parkinson’s disease using fNIRS. <em>Brain Organoid and Systems Neuroscience Journal</em>, <em>2</em>, 23–30. <a href="https://doi.org/10.1016/j.bosn.2024.04.001">https://doi.org/10.1016/j.bosn.2024.04.001</a></div> </div> </div> </div> </div> </div> </div> </div>
Quality of Life of Breast Cancer Patients in Albania
<p>Quality of Life of Breast Cancer Patients in Albania. <span>For this study, the European Organization for Research and Treatment of Cancer Quality of Life (EORTC QLQ – C30) questionnaire was used</span></p>
CyTOF data of PBMC samples of patients with metastatic pancreatic ductal adenocarcinoma
<p>These two CyTOF datasets are a part of the manuscript by M. Baretti "E<span>ntinostat in combination with nivolumab in metastatic pancreatic ductal adenocarcinoma: a phase 2 clinical trial" accepted in Nature Communications. The datasets contain FCS files of PBMCs samples of patients with metastatic pancreatic ductal adenocarcinoma treated with entinostat and nivolumab. PBMC samples were run with myeloid- and lymphoid-oriented panels.<br></span></p>
Continuous monitoring of patient mobility for 18 months using inertial sensors following traumatic knee injury: a case study
<p><strong>This repository contains raw data relating to: </strong>Continuous monitoring of patient mobility for 18 months using inertial sensors following traumatic knee injury: a case study Mueller A., Hoefling H., Nuritdinow T., et al. DOI: 10.1159/000490919</p> <p><strong>Metadata and processed data derived from the raw data deposited here is available here:</strong> https://github.com/Novartis/mueller_et_al_2018</p> <p><strong>Article Abstract</strong></p> <p>Continuous patient activity monitoring during rehabilitation, enabled by digital technologies, will allow the objective capture of real-world mobility and aligning treatment to each individual’s recovery trajectory in real time. To explore the feasibility and added value of such approaches, we present a case study of a 36-year-old male participant monitored continuously for activity levels and gait parameters using a waist-worn inertial sensor following a tibial plateau fracture on the right side, sustained as a result of a high-energy trauma during a sporting accident. During rehabilitation, data were collected for a period of 553 days, with > 80% daytime compliance, until the participant returned to near full mobility. The participant completed a daily diary with the annotation of major events (falls, near falls, cycling periods, or physiotherapy sessions) and key dates in the patient’s recovery, including medical interventions, transitioning off crutches, and returning to work. We demonstrate the feasibility of collecting, storing, and mining of continuous digital mobility data and show that such data can detect changes in mobility and provide insights into long-term rehabilitation. We make both raw data and annotations available as a resource with the aspiration that further methods and insights will be built on this initial exploration of added value and continue to demonstrate that continuous monitoring can be deployed to aid rehabilitation.</p>
Keystroke timing and pressure data captured during touchscreen typing by early Parkinson's disease patients and healthy controls
<p><strong>DATASET</strong></p> <p>The present dataset comprises keystroke timing and pressure data that correspond to short text excerpts typed by early Parkinson’s disease (PD) patients (n=18) and healthy controls (n=15) on a common touchscreen-equipped smartphone (LG Nexus 5X with a screen of 5.2 inches in diagonal and a resolution of 1080 × 1920 pixels, running native Android 7.0). Subjects were asked to transcribe up to 11 short text excerpts, with the initial one being 200 characters-long and common for all subjects, while the rest were 40-115 characters-long, pseudorandomly drawn from the fairy tale 'The Little Prince'. Data were recorded using a custom Android Operating System input method (keyboard), developed for the purposes of the study. Additional details on exepriment design, material and methods can be found in the related research article mentioned below. </p> <p>Data consist of sequences of raw press and release timestamps (in milliseconds), as well as of values of normalized pressure (0.000-1.000) applied to initiate keystrokes, corresponding to the consecutive keys tapped during the transcription of each text excerpt. Data included in the 'Data' folder are organised in sub-folders per subject. Each sub-folder contains a number of .txt files with each one corresponding to a text excerpt typed by the particular subject. Files are named using the format S##_TEX##.txt, with S## denoting the subject's coded ID and TEX## the serial number of the transcribed text excerpt. For all subjects, file S##_TEX01.txt corresponds to the initial and common 200 characters-long text excerpt. Each file contains the sequences of raw key press/release timestamps (Tp#, Tp#) and normalized pressure (NP#), applied to initiate each keystroke, in the following format:</p> <p>{<br> Press, Tp1, Release, Tr1, NP1<br> Press, Tp2, Release, Tr2, NP2<br> .<br> .<br> . <br> Press, Tpn, Release, Trn, NPn<br> }</p> <p>where 1,2,...,n denote the serial index of the key tapped during typing.</p> <p><em>Note:</em> Out of 33 subjects, 32 managed to transcribe 8 to 11 text excerpts, while the remaining one (Subject ID: 16) typed only 5. Ten subjects (Subject IDs: 6, 14, 16, 17, 25, 27, 29, 31, 32, 33) did not manage to type the initial 200 characters-long excerpt in its entirety.</p> <p>The dataset also includes a record, in Microsoft Excel format (Demographics_Clinical_Characteristics.xlsx), of the demographic and clinical characteristics (with respect to PD) of subjects. Entries of the Excel file are linked to subjects' sub-folders and individual keystroke data text files via the coded ID of the subject.</p> <p>Demographic characteristics included:</p> <p>Age; Gender; Education level; Years of smartphone usage; Dominant hand<sup>1</sup></p> <p>Clinical characteristics included:</p> <p>Group (PD, Control); Years from diagnosis; Hoehn-Yahr disease stage; Most affected side<sup>2</sup>; Levodopa Equivalent Daily Dose; UPDRS_III<sup>3</sup> total score; UPDRS_III Item 21 Tremor-Right hand; UPDRS_III Item 21 Tremor-Left hand; UPDRS_III Item 22 Rigidity-Right hand; UPDRS_III Item 22 Rigidity-Left hand; UPDRS_III Item 23 Finger taps-Right hand; UPDRS_III Item 23 Finger taps-Left hand; UPDRS_III Item 31 Body bradykinesia/ Hypokinesia</p> <p><sup>1</sup>Dominant hand: (Relating to handedness) the operant hand generally used for performing fine motor-skills tasks.<br> <sup>2</sup>Most affected body side by Parkinson's disease<br> <sup>3</sup>UPDRS_III: Unified Parkinson's Disease Rating Scale Part III (Motor section)</p> <p> </p> <p><strong>RELATED RESEARCH</strong></p> <p>This dataset was originally used and described in the OPEN ACCESS publication: </p> <p>[1] Iakovakis, D., Hadjidimitriou, S., Charisis, V., Bostantzopoulou, S., Katsarou, Z., & Hadjileontiadis, L. J. (2018). Touchscreen typing-pattern analysis for detecting fine motor skills decline in early-stage Parkinson’s disease. Scientific reports, 8(1), 7663. <a href="http://doi.org/10.1038/s41598-018-25999-0">https://doi.org/10.1038/s41598-018-25999-0</a> </p> <p>All documents and papers that report on research that uses this dataset will acknowledge this by citing the above publication.</p> <p> </p> <p><strong>ETHICS & FUNDING</strong></p> <p>The study during which the present dataset was collected was approved by the Aristotle University of Thessaloniki Bioethics Committee of Medical School (approval no. 359/3.4.17), Thessaloniki, Greece. Informed consent, including permission for third-party access to pseudo-anonymised data, was obtained from all subjects prior to their engagement with the study. The work has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No 690494 - i-PROGNOSIS: Intelligent Parkinson early detection guiding novel supportive interventions (<a href="http://www.i-prognosis.eu">i-prognosis.eu</a>).</p> <p> </p> <p><strong>CORRESPONDANCE</strong></p> <p>Any inquiries regarding this dataset should be adressed to:</p> <p>Mr. Dimitrios Iakovakis (Electrical & Computer Engineer, PhD candidate)</p> <p>Signal Processing & Biomedical Technology Unit<br> Department of Electrical & Computer Engineering<br> Aristotle University of Thessaloniki<br> University Campus, Building D, 6th floor<br> Thessaloniki, Greece, GR54124</p> <p>Tel: +30 2310 996319<br> Fax: +30 2310 996312<br> E-mail: dimiiako12@gmail.com</p> <p> </p> <p><strong>LICENSE</strong></p> <p>This is an open access dataset, licensed under Creative Commons Attribution 4.0 International (<a href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</a>).</p> <p> </p> <p><strong>WARRANTY</strong></p> <p>This dataset comes without any warranty. Administrators of this dataset can not be held accountable for any damage (physical, financial or otherwise) caused by the use of this dataset. </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.