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.

Boolean network representation of a continuous-time system and finite-horizon optimal control: application to the single-gene regulatory system for the lac operon

International Journal of Control(2017)10.1080/00207179.2016.1186289Source: DataRank Database

Boolean network representation of a continuous-time system and finite-horizon optimal control: application to the single-gene regulatory system for the lac operon is a research paper published in International Journal of Control (2017). On theSindex it has a DataRank of 0.653. It has been cited 13 times, with 6 citing works in its 1-hop citation network.

N/A

0.653DataRank · unranked

0.653

13 citations · base score 2.6

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 61%Citation Network 39%

Base Score Contribution

0.396

From this paper's citation signal

Citation Network Contribution

0.257

From 5 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.

Genetic regulatory mechanisms in the synthesis of proteins
Journal of Molecular Biology19616,563 citationsDataRank 1.3
The effect of LacI autoregulation on the performance of the lactose utilization system in Escherichia coli
Nucleic Acids Research201330 citationsDataRank 1.2
From Binary to Multivalued to Continuous Models: The lac Operon as a Case Study
Journal of Integrative Bioinformatics20108 citationsDataRank 0.330

Why this DataRank?

DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 61% comes from its base citations and 39% from the citation network (5 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