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7
datasets available to search
ShareScore release 0.9.0
Dataset results
7 results for “node feature”
PubMed-Temporal: A dynamic graph dataset with node-level features
Open the record for dataset details and reuse information.
Benchmarking eliminative radiomic feature selection for head and neck lymph node classification - Supplemental data
<p>Supplementary files for the publication "Benchmarking eliminative radiomic feature selection for head and neck lymph node classification"</p>
Single-Cell Transcriptional Analysis of Murine Mesenteric Lymph Nodes Following Oral Lyso-phosphatidylserine Nanoparticle Administration Reveals Cellular Heterogeneity in Tolerance Features
GEO Series GSE302907. Mus musculus. 3 samples. Type: Expression profiling by high throughput sequencing.
Shared and unique features distinguishing follicular T helper (TFH) and regulatory (TFR) cells from peripheral lypmh node and Peyer's Patches [Agilent-084107]
GEO Series GSE106590. Mus musculus. 8 samples. Type: Expression profiling by array.
Shared and unique features distinguishing follicular T helper (TFH) and regulatory (TFR) cells from peripheral lypmh node and Peyer's Patches
GEO Series GSE106593. Mus musculus. 28 samples. Type: Expression profiling by high throughput sequencing.
Shared and unique features distinguishing follicular T helper (TFH) and regulatory (TFR) cells from peripheral lypmh node and Peyer's Patches [Agilent-048306]
GEO Series GSE106490. Mus musculus. 20 samples. Type: Expression profiling by array.
Dataset related to article "Predictive value of clinical and radiomic features for radiation therapy response in patients with lymph node-positive head and neck cancer"
<p><strong> Abstract</strong></p><p>Background: Prediction of survival and radiation therapy response is challenging in head and neck cancer with metastatic lymph nodes (LNs). Here we developed novel radiomics- and clinical-based predictive models.</p><p>Methods: Volumes of interest of LNs were employed for radiomic features extraction. Radiomic and clinical features were investigated for their predictive value relatively to locoregional failure (LRF), progression-free survival (PFS), and overall survival (OS) and used to build multivariate models.</p><p>Results: Hundred and six subjects were suitable for final analysis. Univariate analysis identified two radiomic features significantly predictive for LRF, and five radiomic features plus two clinical features significantly predictive for both PFS and OS. The area under the curve of receiver operating characteristic curve combining clinical and radiomic predictors for PFS and OS resulted 0.71 (95%CI: 0.60-0.83) and 0.77 (95%CI: 0.64-0.89).</p><p>Conclusions: Radiomic and clinical features resulted to be independent predictive factors, but external independent validation is mandatory to support these findin</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.