Pilot corpus: NIH-funded biomedical datasets. Any DOI can be scored on demand — network effects sharpen as coverage grows.

Forest and Trees: Exploring Bacterial Virulence with Genome-wide Association Studies and Machine Learning

Trends in Microbiology(2021)10.1016/j.tim.2020.12.002Source: DataRank Database

Forest and Trees: Exploring Bacterial Virulence with Genome-wide Association Studies and Machine Learning is a research paper published in Trends in Microbiology (2021). On theSindex it has a DataRank of 0. It has been cited 76 times.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access76 citations

Free full text

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

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (8 grants)

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 (4)

Evan S. Snitkin ORCID,Nathan B. Pincus ORCID,Alan R. Hauser ORCID,Jonathan P. Allen ORCID

Live enrichment

National Institutes of Health

Grant: R21 AI129167

National Institutes of Health

Grant: RO1 AI148259-01

National Institutes of Health

Grant: U19 AI135964

National Institute of Allergy and Infectious Diseases

Grant: F32 AI108247

National Institute of Allergy and Infectious Diseases

Grant: K24 AI04831

National Institute of Allergy and Infectious Diseases

Grant: R21 AI153953

National Institute of Allergy and Infectious Diseases

Grant: RO1 AI118257

American Heart Association

Grant: 15POST25830019