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Classification of bacterial nanowire proteins using Machine Learning and Feature Engineering model

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.05.03.539336Source: DataRank Database

Classification of bacterial nanowire proteins using Machine Learning and Feature Engineering model is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2023). On theSindex it has a DataRank of 0.180. It has been cited 2 times, with 1 citing works in its 1-hop citation network.

N/A

0.180DataRank · unranked

Scored on demand from live citation data

Open Access2 citations · 1 citing works in its network

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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)OA: greenTopics (20)IDs (PubMed, OpenAlex)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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DataRank Breakdown

Base Score 92%Citation Network 8%

Base Score Contribution

0.165

From this paper's citation signal

Citation Network Contribution

0.0149

From 1 citing papers with measurable signal

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Top 1 citer driving the network score

Ranked by each citer's contribution to N(p) — log1p(C_q) divided by its reference count — out of 1 citer.

Advances and insights into modeling extracellular electron transfer in anaerobic bioprocesses
The Science of The Total Environment20258 citations125 referencesContributes 0.018

Authors (9)

Vincent Peta ORCID,Alain Bertrand Bomgni ORCID,Tuyen Do ORCID,Kalimuthu Jawaharraj ORCID,David R. Salem ORCID

Live enrichment

PubMed:37205598 OpenAlex:https://openalex.org/W4372258260

National Science Foundation

Grant: 1849206

RII Track-1: Building on The 2020 Vision: Expanding Research, Education and Innovation in South Dakota

National Institutes of Health

Grant: 3P20GM103443-22S1

Accelerated aging in late onset Alzheimer’s Disease

National Science Foundation

Grant: 1920954

RII Track-2 FEC: Data Driven Material Discovery Center for Bioengineering Innovation

green

repositoryhttps://www.biorxiv.org/content/biorxiv/early/2023/05/05/2023.05.03.539336.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2023.05.03.539336

repositoryhttps://doi.org/10.1101/2023.05.03.539336

repositoryhttps://pubmed.ncbi.nlm.nih.gov/37205598

Fields of Study

Microbial Fuel Cells and BioremediationCorrosion Behavior and InhibitionBacterial biofilms and quorum sensing0206 medical engineering02 engineering and technology

Keywords

GeobacterSupport vector machineShewanellaRandom forestNanowireElectron transferMaterials scienceComputer scienceArtificial intelligenceComputational biologyNanotechnologyChemistryBiologyBacteriaGenetics

Sustainable Development Goals

SDG 0: Life in Land