Pilot corpus: NIH-funded biomedical datasets. Any DOI can be scored on demand — network effects sharpen as coverage grows.
A Benchmarking Study of Random Projections and Principal Components for Dimensionality Reduction Strategies in Single Cell Analysis
A Benchmarking Study of Random Projections and Principal Components for Dimensionality Reduction Strategies in Single Cell Analysis is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2025). On theSindex it has a DataRank of 0. It has been cited 1 time.
N/A
Scored on demand from live citation data
Open Access1 citations
Download PDF
Cite:
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
›Methodology & internals
Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring
Enrichment:OA: greenIDs (PubMed)
FAIR Checklist
Context only (not used in score)Findable (1/2)
- Has DOI
Accessible (1/2)
- Open Access
Interoperable (0/2)
Reusable (0/3)
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Run a calibrated FAIR evaluation for this paper →
We only score data papers we can read in full — never from an abstract alone.
Authors (2)
Live enrichment