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Prediction and validation of nanowire proteins in Oleidesulfovibrio alaskensis G20 using machine learning and feature engineering

Computational and Structural Biotechnology Journal(2025)10.1016/j.csbj.2025.04.022Source: DataRank Database

Prediction and validation of nanowire proteins in Oleidesulfovibrio alaskensis G20 using machine learning and feature engineering is a research paper published in Computational and Structural Biotechnology Journal (2025). On theSindex it has a DataRank of 0.165. It has been cited 2 times.

N/A

0.165DataRank · unranked

Scored on demand from live citation data

Open Access2 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (7 grants)Impact (FWCI 0.78)OA: goldTopics (26)IDs (PubMed, PMC, OpenAlex)Annotations (4)

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 100%Citation Network 0%

Base Score Contribution

0.165

From this paper's citation signal

Citation Network Contribution

Citation network not refreshed for this result

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Authors (10)

Vincent Peta ORCID,Alain Bertrand Bomgni ORCID,Shiva Aryal ORCID,D. Tuyen ORCID,Kalimuthu Jawaharraj ORCID

Live enrichment

PubMed:40391298 PMC:PMC12088768 OpenAlex:https://openalex.org/W4409590030

National Science Foundation

Grant: 1849206

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

National Science Foundation

Grant: 1920954

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

National Science Foundation

Grant: 2022

National Science Foundation

Grant: 2DBEST

NIH

Grant: P20GM103443

National Institutes of Health

Grant: 3P20GM103443-22S1

Accelerated aging in late onset Alzheimer’s Disease

National Institute of General Medical Sciences

FWCI

0.78

Citation Percentile

0.7%

Citation Trend

2025

2026

goldLicense: cc-by

journalhttps://doi.org/10.1016/j.csbj.2025.04.022

publisherhttps://doi.org/10.1016/j.csbj.2025.04.022

publisherhttps://api.elsevier.com/content/article/PII:S2001037025001436?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S2001037025001436?httpAccept=text/plain

publisherhttps://spj.science.org/doi/pdf/10.1016/j.csbj.2025.04.022

Fields of Study

Machine Learning in BioinformaticsGenomics and Phylogenetic StudiesRNA and protein synthesis mechanisms0206 medical engineering02 engineering and technology

Keywords

Feature engineeringFeature (linguistics)NanowireComputer scienceArtificial intelligenceMachine learningData miningComputational biologyDeep learningNanotechnologyBiologyMaterials scienceBiofilmgene ontologyRandom ForestBacterial NanowiresBiologically Informed Neural NetworkProtein Sequence-based PredictionTP248.13-248.65BiotechnologyResearch Article