Mouse IDGenes: a reference database for genetic interactions in the developing mouse brain is a dataset published in Database (2014). On theSindex it has a DataRank of 0.165, placing it in the top 70.2% of the data-sharing corpus. It has been cited 2 times. Its calibrated FAIR score is 41/100.
Ranks in the top 70% 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=0, pmcid=True, pmid=True
no OpenAlex id
The paper provides a human-readable description of the database structure, but no explicit mention of machine-readable metadata (e.g., XML/JSON-LD schema) or formal metadata standards (e.g., Dublin Core, schema.org) is made.
Open Access
0 OA location(s)
The database URL is given (http://mouseidgenes.helmholtz-muenchen.de) and data can be downloaded as tab-delimited flat files, but no formal access protocol (e.g., REST API, SPARQL endpoint) nor persistent identifiers for individual records are described.
linked_datasets=0, datacite=0
accessions=0, trials=0
The paper uses EMAP/EMAPA ontology identifiers, MGI gene symbols and links to NCBI, UCSC and Ensembl, but does not define standardized vocabularies for interaction types or provide formal machine-readable representation in standard formats like RDF or OWL.
no license
downloads=0
no version chain
is_dataset
The paper states the database is freely available under a CC BY 4.0 license and provides downloads, but does not describe a formal data-availability statement for the paper itself, nor does it deposit data in a long-term repository or provide explicit reproducibility instructions for the machine learning analysis.
Calibrated FAIR score — a parallel quality metric, independent of the DataRank citation score. See the full evaluation →
Base Score Contribution
0.165
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →FWCI
0.13
Citation Percentile
0.4%
Citation Trend
Fields of Study
MeSH Terms
Keywords