Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
189
datasets available to search
ShareScore release 0.9.0
Dataset results
189 results for “feature model”
A patient-derived ccRCC model that retains native stromal features to assess fibrosis-driven personalized therapeutic response
GEO Series GSE315653. Gallus gallus; Homo sapiens. 7 samples. Type: Expression profiling by high throughput sequencing.
A gel-top model for characterizing the mesenchymal features of glioblastoma cells
GEO Series GSE292931. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing.
A novel Induced-recurrence PDX model recapitulates epi-genomic features of Glioblastoma recurrence [RNA-seq]
GEO Series GSE271620. Homo sapiens. 46 samples. Type: Expression profiling by high throughput sequencing.
Modeling Liver Cancer Molecular and Histological Features by CRISPR Editing of Primary Porcine Hepatocytes
GEO Series GSE311743. Sus scrofa. 45 samples. Type: Expression profiling by high throughput sequencing.
A novel Induced-recurrence PDX model recapitulates epi-genomic features of Glioblastoma recurrence [scRNA-seq]
GEO Series GSE271619. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
HybridCAD: A Comprehensive Dataset for Hybrid Additive-Subtractive Manufacturing Feature Recognition in B-Rep CAD Models
<p>The <em>HybridCAD</em> dataset is a novel resource tailored for hybrid additive-subtractive feature recognition in Computer-Aided Design (CAD) models, uniquely combining features from both manufacturing processes. Building on the <em>MFCAD</em> and <em>MFCAD++</em> datasets, <em>HybridCAD</em> introduces additive manufacturing features alongside traditional subtractive ones, enabling the exploration and development of machine learning models for more complex, hybrid manufacturing applications. This dataset is especially suited for automatic feature recognition (AFR) research and model training in hybrid manufacturing contexts.</p> <h3>Dataset Composition</h3> <p>The dataset consists of 8,938 Boundary Representation (B-Rep) CAD models distributed into three main directories:</p> <ol> <li> <p><strong>STEP Files</strong>:</p> <ul> <li>Contains CAD models in STEP format, each representing a distinct part with hybrid manufacturing features.</li> <li>Generated using PythonOCC CAD software, these CAD files serve as the foundation for feature recognition tasks.</li> </ul> </li> <li> <p><strong>Feature Labels</strong>:</p> <ul> <li><strong>File</strong>: <code>feature_labels.txt</code></li> <li>Provides unique label IDs for each B-Rep face in every CAD model, denoting the manufacturing feature name it belongs to.</li> <li>Each CAD model face is labelled according to one of 29 hybrid additive-subtractive features, allowing for accurate and detailed feature recognition.</li> </ul> <ul> <li> </li> </ul> </li> <li> <p><strong>Hierarchical B-Rep Graphs</strong>:</p> <ul> <li>Stored in HDF5 format for structured access to B-Rep data.</li> <li>Detailed structural information is available in <code>h5_structure.txt</code>, explaining the hierarchical arrangement of B-Rep graphs.</li> </ul> </li> </ol> <h3>Dataset Splits</h3> <p>The dataset is split into training, validation, and testing sets as follows:</p> <ul> <li><strong>Training Set</strong>: 6,256 samples (70%)</li> <li><strong>Validation Set</strong>: 1,342 samples (15%)</li> <li><strong>Testing Set</strong>: 1,340 samples (15%)</li> </ul> <h3>Hybrid Manufacturing Features</h3> <p><em>HybridCAD</em> includes a diverse range of additive and subtractive manufacturing features, expanding beyond the subtractive-only features of <em>MFCAD++</em>. This inclusion enables the exploration of hybrid manufacturing processes and the recognition of a broader feature set in CAD models. The complete feature list includes:</p> <p>Label Feature<br>0 Chamfer<br>1 Through hole<br>2 Triangular passage<br>3 Rectangular passage<br>4 6-sided passage<br>5 Triangular through slot<br>6 Rectangular through slot<br>7 Circular through slot<br>8 Rectangular through step<br>9 2-sided through step<br>10 Slanted through step<br>11 O-ring<br>12 Blind hole<br>13 Triangular pocket<br>14 Rectangular pocket<br>15 6-sided pocket<br>16 Circular end pocket<br>17 Rectangular blind slot<br>18 Vertical circular end blind slot<br>19 Horizontal circular end blind slot<br>20 Triangular blind step<br>21 Circular blind step<br>22 Rectangular blind step<br>23 Round<br>24 Extrude cylinder<br>25 Extrude rectangle<br>26 Extrude triangle<br>27 Extrude hexagon<br>28 Extrude pentagon<br>29 Stock</p>
Pathophysiological features of disease in a large animal model of COPD
GEO Series GSE242416. Ovis aries. 54 samples. Type: Expression profiling by high throughput sequencing.
RNA-targeting Cas9 corrects molecular and physiological features in pre-clinical model of myotonic dystrophy type 1
GEO Series GSE152033. Mus musculus. 14 samples. Type: Expression profiling by high throughput sequencing.
Supplementary Material for "Assessing the Impact of Groundwater Saturation Excess Runoff on Hydrologic Features and Processes in a Watershed Modeling Setting"
Open the record for dataset details and reuse information.
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.