元数据
背景(考古学)
代谢组
计算机科学
代谢组学
数据科学
情报检索
数据挖掘
计算生物学
精密医学
化学数据库
R包
作者
Yasin El Abiead,Jeong In Seo,Vincent Charron‐Lamoureux,Michael Strobel,Wilhan Donizete Gonçalves Nunes,Haoqi Nina Zhao,Kine Eide Kvitne,Simone Zuffa,Helena Mannochio-Russo,Harsha Gouda,Cristina Bez,Abubaker Patan,Shipei Xing,Jasmine Zemlin,Ipsita Mohany,Julius Agongo,Andres Mauricio Caraballo Rodriguez,Lindsey A. Burnett,Victoria Deleray,Abzer K Pakkir Shah
标识
DOI:10.1038/s41587-026-03082-8
摘要
Searching and learning from aggregated public metabolomics data spanning thousands of studies remained largely inaccessible. Here we present StructureMASST, a web-based application enabling scalable, structure-centric searches across public metabolomics repositories using molecule names or chemical representations. It queries a precomputed knowledgebase of 2.19 billion spectral matches and 420 million metadata links, supports modification-tolerant and mass-shift searches, and maps chemical structures across taxonomy, biological context and environmental conditions to accelerate discovery.
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