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.

Are Most Human-Specific Proteins Encoded by Long Noncoding RNAs?

Journal of Molecular Evolution(2024)10.1007/s00239-024-10174-zSource: DataRank Database

Are Most Human-Specific Proteins Encoded by Long Noncoding RNAs? is a research paper published in Journal of Molecular Evolution (2024). On theSindex it has a DataRank of 0.169. It has been cited 2 times, with 2 citing works in its 1-hop citation network.

N/A

0.169DataRank · unranked

0.169

2 citations · base score 1.1

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 98%Citation Network 2%

Base Score Contribution

0.165

From this paper's citation signal

Citation Network Contribution

3.92 × 10⁻³

From 1 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.

UCSF Chimera—A visualization system for exploratory research and analysis
Journal of Computational Chemistry200447,376 citationsDataRank 1.6
BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs
Bioinformatics201514,298 citationsDataRank 1.4
AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models
Nucleic Acids Research20218,161 citationsDataRank 14.9Top 13%
UniProt: the universal protein knowledgebase in 2021
20207,014 citationsDataRank 16.0Top 11%
Standardized annotation of translated open reading frames
Nature Biotechnology2022245 citationsDataRank 3.5Top 31%

Why this DataRank?

DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 98% comes from its base citations and 2% 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.

Read the full methodology →

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