Systematic Mining of Bioactive Compounds for Wound Healing From Cayratia Japonica Exosome-Like Nanovesicles: A Workflow Combining LC-MS and DeepSeek Models

A self-designed multimodal framework of LC-MS, combined with DeepSeek models, rapidly and accurately identifies naturally active compounds from CJ-ELNs. This AI-powered system innovatively integrates the traditional analytical technique with modern LLMs, thus greatly favoring data mining of active ingredients in traditional Chinese medicine herbs.

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Publication Details

Journal
JMIR Bioinformatics and Biotechnology
Published
2026-01-08
DOI
https://doi.org/10.2196/80539
Primary Topic
Extracellular vesicles in disease
Type
article
Field-Weighted Citation Impact
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article

Systematic Mining of Bioactive Compounds for Wound Healing From Cayratia Japonica Exosome-Like Nanovesicles: A Workflow Combining LC-MS and DeepSeek Models

Qiaojing Yan, Yuping Fan, Qiang Fu, Jian Yao et al.
JMIR Bioinformatics and Biotechnology
Extracellular vesicles in disease
article

Systematic Mining of Bioactive Compounds for Wound Healing From Cayratia Japonica Exosome-Like Nanovesicles: A Workflow Combining LC-MS and DeepSeek Models

Qiaojing Yan, Yuping Fan, Qiang Fu, Jian Yao, Wei Ji, Ming-Xia Song
article en

Abstract

A self-designed multimodal framework of LC-MS, combined with DeepSeek models, rapidly and accurately identifies naturally active compounds from CJ-ELNs. This AI-powered system innovatively integrates the traditional analytical technique with modern LLMs, thus greatly favoring data mining of active ingredients in traditional Chinese medicine herbs.

JMIR Bioinformatics and BiotechnologyVol. 7
Jinggangshan University (CN), Université de Montpellier (FR), University of Yamanashi (JP), Southeast University (CN)
Openalex Percentile: Top 92%
Extracellular vesicles in disease
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