Compare
Protein Data Bank vs COCO 2017
Side-by-side comparison of Protein Data Bank (Dataset) and COCO 2017 (Dataset).
Live Data← All Comparisons
81.9
Composite Score
Protein Data Bank
Dataset · RCSB PDB / wwPDB Consortium
82.5
Composite Score
COCO 2017
Dataset · Microsoft
Overall Winner
COCO 2017
Protein Data Bank wins 2 of 6 categories · COCO 2017 wins 2 of 6 categories
Score Comparison
Protein Data BankvsCOCO 2017
Composite
81.9:82.5
Adoption
95:97
Quality
97:96
Freshness
91:65
Citations
98:98
Engagement
0:0
Details
FieldProtein Data BankCOCO 2017
TypeDatasetDataset
ProviderRCSB PDB / wwPDB ConsortiumMicrosoft
Version20262017
Categoryscientificcomputer-vision
Pricingfreefree
LicenseCC0 1.0CC-BY-4.0
DescriptionThe RCSB Protein Data Bank (PDB) is the single worldwide archive of experimentally determined 3D structures of proteins, nucleic acids, and complex assemblies, currently containing over 220,000 biological macromolecular structures determined by X-ray crystallography, NMR, and cryo-EM. It is the foundational structural dataset for computational biology and was used to train and validate AlphaFold2 and other structure-prediction models.Microsoft COCO (Common Objects in Context) 2017 provides 118K training images with 860K object instances annotated with bounding boxes, segmentation masks, keypoints, and captions across 80 object categories. It remains the primary benchmark for object detection and instance segmentation research.
Capabilities
Only Protein Data Bank
3d-structure-searchsequence-structure-mappingligand-binding-analysis
Shared
None
Only COCO 2017
object-detectioninstance-segmentationkeypoint-detectionimage-captioning
Integrations
Only Protein Data Bank
biopythonpymolalphafold
Shared
None
Only COCO 2017
PyTorchTensorFlowDetectron2MMDetection
Tags
Only Protein Data Bank
proteinsstructuresbiologycrystallographyalphafold
Shared
None
Only COCO 2017
object-detectionsegmentationkeypointscaptionsbenchmark
Use Cases
Protein Data Bank
- ▸protein structure prediction training
- ▸drug design
- ▸structural biology research
COCO 2017
- ▸model training
- ▸benchmark
- ▸computer vision research
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