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.

Measurement and Analysis of Lysine Acetylation by KAT Complexes In Vitro and In Vivo

Methods in Molecular Biology(2019)10.1007/978-1-4939-9434-2_5Source: DataRank Database

Measurement and Analysis of Lysine Acetylation by KAT Complexes In Vitro and In Vivo is a research paper published in Methods in Molecular Biology (2019). On theSindex it has a DataRank of 0.225. It has been cited 3 times, with 2 citing works in its 1-hop citation network.

N/A

0.225DataRank · unranked

0.225

3 citations · base score 1.4

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 (1/2)

Has DOI

Accessible (0/2)

Interoperable (0/2)

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 92%Citation Network 8%

Base Score Contribution

0.208

From this paper's citation signal

Citation Network Contribution

0.0172

From 1 citing papers with measurable signal

Learn more about DataRank methodology →

Top 1 citer driving the network score

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

RNA synthesis and histone acetylation during the course of gene activation in lymphocytes.
Proceedings of the National Academy of Sciences1966449 citationsDataRank 0.916

Why this DataRank?

DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 92% comes from its base citations and 8% from the citation network (1 citing paper 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.

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

Authors (3)

Jean-Philippe Lambert,Jacques Côté,Anahita Lashgari