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Deep autoencoder as an interpretable tool for Raman spectroscopy investigation of chemical and extracellular vesicle mixtures

Biomedical Optics Express(2024)10.1364/boe.522376Source: DataRank Database

Deep autoencoder as an interpretable tool for Raman spectroscopy investigation of chemical and extracellular vesicle mixtures is a research paper published in Biomedical Optics Express (2024). On theSindex it has a DataRank of 0.569. It has been cited 15 times, with 15 citing works in its 1-hop citation network.

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0.569DataRank · unranked

Scored on demand from live citation data

Deposits data Open Access15 citations · 15 citing works in its network

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Data availability

Repositories this paper deposited data in (declared in PubMed).

figshare10.6084/m9.figshare.25712505

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (11 grants)Impact (FWCI 2.57)OA: goldTopics (27)IDs (PubMed, PMC, 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)

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DataRank Breakdown

Base Score 73%Citation Network 27%

Base Score Contribution

0.416

From this paper's citation signal

Citation Network Contribution

0.153

From 9 citing papers with measurable signal

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Top 5 citers driving the network score

Ranked by each citer's contribution to N(p) — log1p(C_q) divided by its reference count — out of 15 citers.

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Biosensors and Bioelectronics202417 citations112 referencesContributes 0.026
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Journal of Nanobiotechnology202623 citations396 referencesContributes 0.008

Authors (13)

Miguel Martínez-Calderón ORCID,Robert Otupiri ORCID,Anastasiia Artuyants ORCID,MoiMoi Lowe,Xia Ning ORCID

Live enrichment

PubMed:39022543 PMC:PMC11249694 OpenAlex:https://openalex.org/W4396222345

University of Auckland

Grant: Hub for Extracellular Vesicle Investigations

College of Engineering, Ohio State University

Grant: LEGACY Postdoctoral Scholars Program

Breast Cancer Foundation New Zealand

Grant: Innovation and Technology Project Grant

National Institutes of Health

Grant: K99EB033857

National Institutes of Health

Grant: R01GM109988

National Institutes of Health

Grant: U18TR003807

National Institutes of Health

Grant: UG3/UH3TR002884

National Institutes of Health

Grant: 1U18TR003807-01

Multi-parametric Integrated Molecular Detection of SARS-CoV-2 from Biofluids by Adapting Single Extracellular Vesicle Characterization Technologies

National Institutes of Health

Grant: 5R01GM109988-06

Targeted TERS Investigations of Ligand-Receptor Binding

National Institutes of Health

Grant: 5UH3TR002884-04

Microfluidics Array Based Sorting, Isolation, and RNA Analysis in Single Extracellular V csicles

National Institutes of Health

Grant: 1K99EB033857-01

Machine Learning-enabled Classification of Extracellular Vesicles Using Nanoplasmonic Microfluidics

FWCI

2.57

Citation Percentile

0.9%

Citation Trend

2024

2025

2026

goldLicense: https://doi.org/10.1364/OA_License_v2#VOR-OA

journalhttps://doi.org/10.1364/boe.522376

publisherhttps://doi.org/10.1364/boe.522376

publisherhttps://opg.optica.org/viewmedia.cfm?URI=boe-15-7-4220&seq=0

repositoryhttps://pubmed.ncbi.nlm.nih.gov/39022543

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/11249694

Fields of Study

Extracellular vesicles in diseaseSpectroscopy Techniques in Biomedical and Chemical ResearchPhotoacoustic and Ultrasonic Imaging0301 basic medicine0303 health sciences03 medical and health sciences

Keywords

Raman spectroscopyAutoencoderBiological systemExtracellular vesiclesSpectroscopyChemical imagingPrincipal component analysisComputer scienceMaterials scienceArtificial intelligenceNanotechnologyPattern recognition (psychology)Analytical Chemistry (journal)Deep learningChemistryHyperspectral imagingBiologyOpticsChromatographyPhysicsArticle