🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge
Demo corpus. Scores are computed on a select set of biomedical paper/datasets and may be inaccurate for papers outside this corpus — DataRank relies on network effects that improve with scale. We aim to expand this into a fully open resource pending additional funding.

KEGG as a reference resource for gene and protein annotation

Nucleic Acids Research(2015)10.1093/nar/gkv1070Source: DataRank Database
Top 1%
15.8DataRank
15.8Top 1%
Dataset Open Access
7573 citations · base score 8.9
datarank_citation_only_1hop_v4Methodology
Data sources & pipeline
Pipeline:CrossRefSciBERTdoi-metadataOpenAlexDataRank
Enrichment:Pending
FAIR ChecklistContext only (not used in score)
FFindable
Has DOI
AAccessible
Open Access
IInteroperable
RReusable
Dataset classification

FAIR checklist signals are shown for context only and do not affect DataRank scoring.

DataRank Breakdown

Base Component 8%Network Component 92%

Base Score Contribution

1.3

From this paper's citation signal

Citation Network Contribution

14.5

From 197 citing papers with measurable signal

Learn more about DataRank methodology →

Authors (5)

Yoko SatoORCID,Masayuki Kawashima,Miho Furumichi,Mao Tanabe,Minoru KanehisaORCID

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