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Forward-predictive SERS-based chemical taxonomy for untargeted structural elucidation of epimeric ce...

Forward-predictive SERS-based chemical taxonomy for untargeted structural elucidation of epimeric ce...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_8bd317472e0a40fdba2c4672842a463f

Forward-predictive SERS-based chemical taxonomy for untargeted structural elucidation of epimeric cerebrosides

About this item

Full title

Forward-predictive SERS-based chemical taxonomy for untargeted structural elucidation of epimeric cerebrosides

Publisher

London: Nature Publishing Group UK

Journal title

Nature communications, 2024-03, Vol.15 (1), p.2582-14, Article 2582

Language

English

Formats

Publication information

Publisher

London: Nature Publishing Group UK

More information

Scope and Contents

Contents

Achieving untargeted chemical identification, isomeric differentiation, and quantification is critical to most scientific and technological problems but remains challenging. Here, we demonstrate an integrated SERS-based chemical taxonomy machine learning framework for untargeted structural elucidation of 11 epimeric cerebrosides, attaining >90% acc...

Alternative Titles

Full title

Forward-predictive SERS-based chemical taxonomy for untargeted structural elucidation of epimeric cerebrosides

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_8bd317472e0a40fdba2c4672842a463f

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_8bd317472e0a40fdba2c4672842a463f

Other Identifiers

ISSN

2041-1723

E-ISSN

2041-1723

DOI

10.1038/s41467-024-46838-z

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