ArticleNature communications2023
Ultra-fast and accurate electron ionization mass spectrum matching for compound identification with million-scale in-silico library.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- DeepMASS v.2: An enhanced deep learning platform for large-scale discovery and structural annotation of unknown plant metabolites.Plant communications · 2026Article
- Article
- SpecTUS: Spectral Translator for Unknown Structures Annotation from EI-MS Spectra.Analytical chemistry · 2026Article
- MutAIverse: an AI-powered, mechanism-backed platform for discovering novel DNA adducts and their precursor genotoxins.Journal of cheminformatics · 2026Article
- Peak2Patch: High-Fidelity Functional Group Identification through Attention-Based Fusion of Infrared and Mass Spectra.ACS omega · 2026Article
- Reimagining invasive weeds through a preliminary antibacterial and phytochemical evaluation of Ipomoea purpurea (L.) Roth floral and seed ethereal extracts.Scientific reports · 2025Article
- Topological segmentation of mass spectrometry imaging data.Journal of mass spectrometry and advances in the clinical lab · 2025Article
- Refining EI-MS library search results through atomic-level insights.Communications chemistry · 2025Article
- A large language model for deriving spectral embeddings for accurate compound identification in mass spectrometry.Communications chemistry · 2025Article
- Simplistic Software for Analyzing Mass Spectra and a Mixed Experimental-Theoretical Database for Identifying Poisonous and Explosive Substances.Journal of computational chemistry · 2025Article
- Discovering organic reactions with a machine-learning-powered deciphering of tera-scale mass spectrometry data.Nature communications · 2025Article
- PSAnalytical chemistry · 2024Article
- Data-Driven Compound Identification in Atmospheric Mass Spectrometry.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Deep-Learning-Based Mixture Identification for Nuclear Magnetic Resonance Spectroscopy Applied to Plant Flavors.Molecules (Basel, Switzerland) · 2023Article
- Ultra-fast and accurate electron ionization mass spectrum matching for compound identification with million-scale in-silico library.Nature communications · 2023Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Spectrum matching is the most common method for compound identification in mass spectrometry (MS). However, some challenges limit its efficiency, including the coverage of spectral libraries, the accuracy, and the speed of matching. In this study, a million-scale in-silico EI-MS library is established. Furthermore, an ultra-fast and accurate spectrum matching (FastEI) method is proposed to substantially improve accuracy using Word2vec spectral embedding and boost the speed using the hierarchical navigable small-world graph (HNSW). It achieves 80.4% recall@10 accuracy (88.3% with 5 Da mass filter) with a speedup of two orders of magnitude compared with the weighted cosine similarity method (WCS). When FastEI is applied to identify the molecules beyond NIST 2017 library, it achieves 50% recall@1 accuracy. FastEI is packaged as a standalone and user-friendly software for common users with limited computational backgrounds. Overall, FastEI combined with a million-scale in-silico library facilitates compound identification as an accurate and ultra-fast tool.
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