CellMarker: a manually curated resource of cell markers in human and mouse is a dataset published in Nucleic Acids Research (2019). On theSindex it has a DataRank of 8.6, placing it in the top 1.8% of the data-sharing corpus. It has been cited 1,736 times, with 100 citing works in its 1-hop citation network. Its calibrated FAIR score is 64/100.
Ranks in the top 2% for downstream scientific impact
Linked data & code
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.
Full FAIR picture · advisory
This score predates the current agent — it came from the earlier rubric, which blended repository metadata into the number and asked the model for a rating rather than an evidenced verdict. Re-evaluate the paper to score it against the current standards-anchored criteria, where every verdict is backed by a quote from the full text.
DOI present
datacite=25, pmcid=True, pmid=True
no OpenAlex id
The paper provides basic bibliographic metadata but lacks rich machine-readable metadata such as structured data markup or extensive metadata beyond standard journal fields.
files/OA location present but not flagged OA
7 OA location(s)
The data access protocol is clear: the database is freely accessible online with no registration, and tab-delimited files are available for download, but no code access is mentioned.
linked_datasets=0, datacite=25
accessions=0, trials=0
The paper uses standard identifiers (Entrez Gene, UniProt, UniProt tissues, Human Cell Atlas) and formats (tab-delimited, MySQL), ensuring interoperability.
no license
downloads=0
no version chain
is_dataset
Data is available under a CC BY-NC 4.0 license, but reproducibility is limited because the full list of curated papers and any processing code are not provided.
Calibrated FAIR score — a parallel quality metric, independent of the DataRank citation score. See the full evaluation →
Base Score Contribution
1.1
From this paper's citation signal
Citation Network Contribution
7.5
From 100 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 100 citers.
National High Technology Research and Development Program of China
Grant: 2014AA021102
National Program on Key Basic Research
Grant: 2014CB910504
National Natural Science Foundation of China
Grant: 61473106
National Natural Science Foundation of China
Grant: 61573122
National Natural Science Foundation of China
Grant: 31601076
China Postdoctoral Science Foundation
Grant: 2016M600260
Harbin Medical University
Grant: WLD-QN1407
Construction of Higher Education in Heilongjiang Province
Grant: UNPYSCT-2016049
Heilongjiang Postdoctoral Foundation
Grant: LBHZ16098
FWCI
0.66
Citation Percentile
0.7%
Fields of Study
MeSH Terms
Keywords
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Additional file 4 of The predicting roles of carcinoembryonic antigen and its underlying mechanism in the progression of coronavirus disease 2019
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