Pilot corpus: NIH-funded biomedical datasets. Any DOI can be scored on demand — network effects sharpen as coverage grows.

Error Bound for Hill-Function Approximations in a Class of Stochastic Transcriptional Network Models

DSpace@MIT (Massachusetts Institute of Technology)(2023)10.1109/cdc49753.2023.10383993Source: DataRank Database

Error Bound for Hill-Function Approximations in a Class of Stochastic Transcriptional Network Models is a research paper published in DSpace@MIT (Massachusetts Institute of Technology) (2023). On theSindex it has a DataRank of 0. It has been cited 1 time.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access1 citations

Download PDF

Cite:

DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?

›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (3 grants)Impact (FWCI 2.65)OA: greenTopics (26)IDs (PubMed, OpenAlex)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

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 →

We only score data papers we can read in full — never from an abstract alone.

Authors (3)

Theodore W. Grunberg ORCID,Domitilla Del Vecchio ORCID,Dylan Hirsch

Live enrichment

PubMed:30945415 OpenAlex:https://openalex.org/W4391020290

Air Force Office of Scientific Research

Grant: FA9550-22-1-0316

National Institutes of Health

Grant: R01-HD105947-03

National Science Foundation

Grant: 1745302

Graduate Research Fellowship Program (GRFP)

FWCI

2.65

Citation Percentile

0.9%

Citation Trend

2025

greenLicense: cc-by-nc

repositoryhttps://dspace.mit.edu/bitstream/1721.1/150329/1/CDC_time_scale_separation_v11-4.pdf

publisherhttp://xplorestaging.ieee.org/ielx7/10383192/10383193/10383993.pdf?arnumber=10383993

repositoryhttps://hdl.handle.net/1721.1/150329

https://doi.org/10.1109/cdc49753.2023.10383993

Fields of Study

Gene Regulatory Network AnalysisProbabilistic and Robust Engineering DesignDiffusion and Search Dynamics0206 medical engineering02 engineering and technology

Keywords

Stochastic processFunction (biology)GeneGene regulatory networkStochastic modellingContext (archaeology)Stochastic approximationMoment-generating functionMathematicsComputational biologyComputer scienceStatistical physicsBiologyProbability density functionGene expressionPhysicsGeneticsStatisticsSystems biologyBiomolecular systemsGenetic regulatory systems