JESTR: Joint Embedding Space Technique for Ranking candidate molecules for the annotation of untargeted metabolomics data

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Publication Details

Journal
Bioinformatics
Published
2025-06-17
DOI
https://doi.org/10.1093/bioinformatics/btaf354
Citations
3
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
Field-Weighted Citation Impact
2.42
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article

JESTR: Joint Embedding Space Technique for Ranking candidate molecules for the annotation of untargeted metabolomics data

Apurva Kalia, Soha Hassoun, Dilip Krishnan, Yan Zhou Chen
3 citations
Bioinformatics
Metabolomics and Mass Spectrometry Studies
2.42
article

JESTR: Joint Embedding Space Technique for Ranking candidate molecules for the annotation of untargeted metabolomics data

Apurva Kalia, Soha Hassoun, Dilip Krishnan, Yan Zhou Chen
article en
3 citations

Abstract

No abstract available for this paper.
BioinformaticsVol. 41(7)
Tufts University (US), Google (United States) (US)
Openalex Percentile: Top 11%
Metabolomics and Mass Spectrometry Studies
2.42
DOIOpen Access PDFOpenAlex
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JESTR: Joint Embedding Space Technique for Ranking candidate molecules for the annotation of untargeted metabolomics data — Apurva Kalia, Soha Hassoun, et al. · Bioinformatics (2025) | TGRS Research Map | TGRS