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.

Structure and functions of the translation initiation factor eIF4E and its role in cancer development and treatment

Journal of Genetics and Genomics(2018)10.1016/j.jgg.2018.01.003Source: DataRank Database

Structure and functions of the translation initiation factor eIF4E and its role in cancer development and treatment is a research paper published in Journal of Genetics and Genomics (2018). On theSindex it has a DataRank of 2.0. It has been cited 67 times, with 65 citing works in its 1-hop citation network.

N/A

2.0DataRank · unranked

2.0

67 citations · base score 4.2

Cite:

datarank_citation_only_1hop_v6· scope data_onlyMethodology

›Data sources & pipeline

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Pending

FAIR Checklist

Context only (not used in score)

Findable (2/2)

Has DOI
Indexed in repositories

Accessible (0/2)

Interoperable (2/2)

DataCite relations
Linked datasets

Reusable (0/3)

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

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DataRank Breakdown

Base Score 31%Citation Network 69%

Base Score Contribution

0.633

From this paper's citation signal

Citation Network Contribution

1.4

From 48 citing papers with measurable signal

Learn more about DataRank methodology →

Top 2 citers driving the network score

Ranked by citation count — the same ordering the engine uses when summing log1p(C_q) over citers.

Control of eukaryotic protein synthesis by upstream open reading frames in the 5′-untranslated region of an mRNA
Biochemical Journal2002319 citationsDataRank 14.0
Cap-Assisted Internal Initiation of Translation of Histone H4
Molecular Cell201197 citationsDataRank 3.4

Why this DataRank?

DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 31% comes from its base citations and 69% from the citation network (48 citing papers contributed measurable signal).

Base score B(p): log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
Network N(p): Σ over citers of log1p(C_q) ÷ max(outdegree_q, 1). Being cited by a highly-cited paper with few references counts most.
Damping factor d = 0.85: DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
Self-citations excluded: Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.

Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.

Read the full methodology →

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Node colors:CenterData PaperData + Open AccessNon-dataSelected & links| Node size = percentile rank