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.

Support Measures to Estimate the Reliability of Evolutionary Events Predicted by Reconciliation Methods

PLoS ONE(2013)10.1371/journal.pone.0073667Source: DataRank Database

Support Measures to Estimate the Reliability of Evolutionary Events Predicted by Reconciliation Methods is a research paper published in PLoS ONE (2013). On theSindex it has a DataRank of 1.9. It has been cited 25 times, with 20 citing works in its 1-hop citation network. Its calibrated FAIR score is 68/100.

N/A

1.9DataRank · unranked

1.9

25 citations · base score 3.3

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.

68FAIR score

F Findable

100

A Accessible

I Interoperable

R Reusable

Top 4% by FAIRdeterministic✓ full text read

Calibrated FAIR score — a parallel quality metric, independent of the DataRank citation score. See the full evaluation →

DataRank Breakdown

Base Score 26%Citation Network 74%

Base Score Contribution

0.489

From this paper's citation signal

Citation Network Contribution

1.4

From 16 citing papers with measurable signal

Learn more about DataRank methodology →

Top 3 citers driving the network score

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

trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses
Bioinformatics200913,256 citationsDataRank 1.4
Efficient algorithms for the reconciliation problem with gene duplication, horizontal transfer and loss
Bioinformatics2012221 citationsDataRank 0.810
An efficient exact algorithm for computing all pairwise distances between reconciliations in the duplication-transfer-loss model
BMC Bioinformatics201912 citationsDataRank 0.494

Why this DataRank?

DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 26% comes from its base citations and 74% from the citation network (16 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

Authors (4)

Vincent Ranwez,Vincent Berry,Celine Scornavacca,Thi-Hau Nguyen

Related Papers (1)

Pareto-optimal phylogenetic tree reconciliation

N/A

0.624DataRank · unranked

Bioinformatics(2014)

co-cited

10.1093/bioinformatics/btu289