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270 results for “Disease Phenotypes”

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ClinicalTrials.gov32/100

An Observational Study of Patients With Lysosomal Acid Lipase Deficiency/Cholesteryl Ester Storage Disease Phenotype

ClinicalTrials.gov study NCT01528917. IPD Sharing: NO. Countries: 8. Publications: 2.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

Correlation Between Clinical and Electrophysiological Phenotypes in a Population of Patients With Neuropathy Charcot-Marie-Tooth Disease Type 1A

ClinicalTrials.gov study NCT01750710. IPD Sharing: Not stated. Countries: 1. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Study of Phenotypic and Functional Characteristics of Regulatory T Lymphocytes in Horton's Disease

ClinicalTrials.gov study NCT02857192. IPD Sharing: Not stated. Countries: 1. Publications: 2.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Longitudinal Evaluation of HIV-associated Lung Disease Phenotypes

ClinicalTrials.gov study NCT02238327. IPD Sharing: Not stated. Countries: 1. Publications: 3.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

The Role of Alcohol Consumption in the Aetiology of Different Cardiovascular Disease Phenotypes: a CALIBER Study

ClinicalTrials.gov study NCT01864031. IPD Sharing: Not stated. Countries: 1. Publications: 6.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Study to Determine Mutations in the Gaucher Gene in Patients With Idiopathic Parkinson's Disease for Phenotype-genotype Correlation

ClinicalTrials.gov study NCT01272687. IPD Sharing: Not stated. Countries: 2. Publications: 13.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Molecular Phenotypes for Cystic Fibrosis Lung Disease

ClinicalTrials.gov study NCT01116414. IPD Sharing: Not stated. Countries: 1. Publications: 4.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

PreDiction and Validation of Clinical CoursE of Coronary Artery DiSease With CT-Derived Non-Invasive HemodYnamic Phenotyping and Plaque Characterization (DESTINY Study)

ClinicalTrials.gov study NCT04794868. IPD Sharing: UNDECIDED. Countries: 2. Publications: 2.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Obesity Phenotypes and Its Relation to Cardiovascular Diseases

ClinicalTrials.gov study NCT06092021. IPD Sharing: Not stated. Countries: 1. Publications: 2.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Cognitive Phenotypes in Parkinson's Disease

ClinicalTrials.gov study NCT01792843. IPD Sharing: NO. Countries: 1. Publications: 1.

closedIPD-NOFeb 2026View details →
dryad32/100

Natural history, phenotypic spectrum, and discriminative features of multisystemic RFC1-disease

Open the record for dataset details and reuse information.

publicDec 2020View details →
dryad32/100

Data associated with 'Metformin rescues Parkinson’s disease phenotypes caused by hyperactive mitochondria'

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publicSep 2020View details →
dryad32/100

Data from: ApoE is a correlate of phenotypic heterogeneity in Alzheimer’s disease in a national cohort

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publicAug 2020View details →
dryad32/100

Data from: Evolutionary epidemiology of schistosomiasis: linking parasite genetics with disease phenotype in humans

Open the record for dataset details and reuse information.

publicNov 2017View details →
dryad28/100

Data from: From cellular characteristics to disease diagnosis: uncovering phenotypes with supercells

Cell heterogeneity and the inherent complexity due to the interplay of multiple molecular processes within the cell pose difficult challenges for current single-cell biology. We introduce an approach that identifies a disease phenotype from multiparameter single-cell measurements, which is based on the concept of "supercell statistics", a single-cell-based averaging procedure followed by a machine learning classification scheme. We are able to assess the optimal tradeoff between the number of single cells averaged and the number of measurements needed to capture phenotypic differences between healthy and diseased patients, as well as between different diseases that are difficult to diagnose otherwise. We apply our approach to two kinds of single-cell datasets, addressing the diagnosis of a premature aging disorder using images of cell nuclei, as well as the phenotypes of two non-infectious uveitides (the ocular manifestations of Behçet's disease and sarcoidosis) based on multicolor flow cytometry. In the former case, one nuclear shape measurement taken over a group of 30 cells is sufficient to classify samples as healthy or diseased, in agreement with usual laboratory practice. In the latter, our method is able to identify a minimal set of 5 markers that accurately predict Behçet's disease and sarcoidosis. This is the first time that a quantitative phenotypic distinction between these two diseases has been achieved. To obtain this clear phenotypic signature, about one hundred CD8+ T cells need to be measured. Although the molecular markers identified have been reported to be important players in autoimmune disorders, this is the first report pointing out that CD8+ T cells can be used to distinguish two systemic inflammatory diseases. Beyond these specific cases, the approach proposed here is applicable to datasets generated by other kinds of state-of-the-art and forthcoming single-cell technologies, such as multidimensional mass cytometry, single-cell gene expression, and single-cell full genome sequencing techniques.

opencc-zeroDec 2012View details →
zenodo28/100

Age-induced midbrain-striatum assembloid models early phenotypes of Parkinson's disease

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opencc-by-4.0Oct 2023View details →
dryad28/100

Association of gyrification pattern, white matter changes and phenotypic profile in patients with Parkinson's disease

<p><b>Objective:</b> To investigate the cortical gyrification changes as well as their relationships with white matter (WM) microstructural abnormalities in the akinetic-rigid (AR) and tremor-dominant (TD) subtypes of Parkinson's disease (PD).</p> <p><b>Methods:</b> Sixty-four patients with the AR subtype, 26 patients with the TD subtype and 56 healthy controls (HCs) were included in this study. High-resolution T1-weighted and diffusion-weighted images were acquired for each participant. We computed local gyrification index (LGI) and fractional anisotropy (FA) to identify the cortical gyrification and WM microstructural changes in the AR and TD subtypes.</p> <p><b>Results: </b>Compared with HCs, patients with the AR subtype showed decreased LGI in the precentral, postcentral, inferior and superior parietal, middle and superior frontal/temporal, anterior and posterior cingulate, orbitofrontal, supramarginal, precuneus, and some visual cortices, and decreased FA in the corticospinal tract, inferior and superior longitudinal fasciculus, inferior fronto-occipital fasciculus, forceps minor/major, and anterior thalamic radiation. Decreases in LGI and FA of the AR subtype were found to be tightly coupled. LGIs of the left inferior and middle frontal gyrus correlated with the mini-mental state examination and the Hoehn and Yahr scores of patients with the AR subtype. Patients with the TD subtype showed no significant change in the LGI and FA compared with patients with the AR subtype and HCs.</p> <p><b>Conclusions:</b> Our results suggest that cortical gyrification changes in PD are motor phenotype-specific and are possibly mediated by the microstructural abnormalities of the underlying WM tracts.</p>

opencc-zeroFeb 2022View details →
ClinicalTrials.gov28/100

INREAL - Nintedanib for Changes in Dyspnea and Cough in Patients Suffering From Chronic Fibrosing Interstitial Lung Disease (ILD) With a Progressive Phenotype in Everyday Clinical Practice: a Real-wor

ClinicalTrials.gov study NCT04702893. IPD Sharing: YES. Countries: 1. Publications: 0.

controlledIPD-YESFeb 2026View details →
ClinicalTrials.gov28/100

Molecular Phenotyping of Asthma in Sickle Cell Disease

ClinicalTrials.gov study NCT01879592. IPD Sharing: NO. Countries: 1. Publications: 0.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov28/100

Metabolic Phenotypes of Obesity and Diabetic Kidney Disease in Patients with Type 2 Diabetes Mellitus

ClinicalTrials.gov study NCT06591104. IPD Sharing: NO. Countries: 0. Publications: 4.

closedIPD-NOFeb 2026View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record