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.

Translational Bioinformatics: Linking the Molecular World to the Clinical World

Clinical Pharmacology & Therapeutics(2012)10.1038/clpt.2012.49Source: DataRank Database

Translational Bioinformatics: Linking the Molecular World to the Clinical World is a research paper published in Clinical Pharmacology & Therapeutics (2012). On theSindex it has a DataRank of 2.7. It has been cited 49 times, with 49 citing works in its 1-hop citation network.

N/A

2.7DataRank · unranked

2.7

49 citations · base score 3.9

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.

Run a calibrated FAIR evaluation for this paper →

DataRank Breakdown

Base Score 22%Citation Network 78%

Base Score Contribution

0.587

From this paper's citation signal

Citation Network Contribution

2.1

From 40 citing papers with measurable signal

Learn more about DataRank methodology →

Top 5 citers driving the network score

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

Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling
Nature20009,923 citationsDataRank 1.4
Clinical assessment incorporating a personal genome
The Lancet2010676 citationsDataRank 0.978
Network-Based Elucidation of Human Disease Similarities Reveals Common Functional Modules Enriched for Pluripotent Drug Targets
PLoS Computational Biology2010340 citationsDataRank 0.875
Challenges in the clinical application of whole-genome sequencing
The Lancet2010232 citationsDataRank 0.818
Personalized Medicine: Challenges and Opportunities for Translational Bioinformatics
Personalized Medicine201375 citationsDataRank 3.8

Why this DataRank?

DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 22% comes from its base citations and 78% from the citation network (40 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 →

Click a node to highlight its connections. Use scroll to zoom. Drag to pan.

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