Single cell transcriptomic profiling identifies molecular phenotypes of newborn human lung cells is a dataset published in bioRxiv (Cold Spring Harbor Laboratory) (2020). On theSindex it has a DataRank of 0.478, placing it in the top 39.9% of the data-sharing corpus. It has been cited 6 times, with 5 citing works in its 1-hop citation network.
Ranks in the top 40% for downstream scientific impact
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full — never from an abstract alone.
Base Score Contribution
0.292
From this paper's citation signal
Citation Network Contribution
0.186
From 4 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 5 citers.
National Institutes of Health
Grant: 5U01HL122700-05
Biorepository for Investigation of Neonatal Diseases of Lung-Normal (BRINDL-NL)
National Institutes of Health
Grant: 5UL1TR002001-08
The University of Rochester Clinical and Translational Science Award Hub
National Institutes of Health
Grant: 5U01HL122642-03
"Lung MAP" Atlas Research Center
Fields of Study
Keywords
Sustainable Development Goals