科研速览 · Science Skim继续刷下去 · Keep skimming →
◆ Methods in molecular biology (Clifton, N.J.)2026-01-01

mzmine: Unifying Mass Spectrometry Data Processing.

Ansgar Korf, Robin Schmid, Steffen Heuckeroth, Tomáš Pluskal

原始摘要(英文原文)· Original abstract
Modern mass spectrometry (MS) experiments generate increasingly complex, multidimensional datasets across diverse analytical modalities, including liquid chromatography (LC)-MS, gas chromatography (GC)-MS, ion mobility spectrometry, and mass spectrometry imaging. Efficient analysis of such heterogeneous data has traditionally required multiple vendor-specific software tools, limiting reproducibility and integration. mzmine 4 addresses this challenge by providing a unified, vendor-neutral, and extensible software platform for comprehensive MS data processing and interpretation. Building on nearly two decades of community-driven development, mzmine 4 introduces substantial improvements in performance, scalability, and usability, enabling the routine analysis of large-scale and multimodal datasets on standard consumer hardware. The software integrates workflows for feature detection, alignment, spectral library matching, molecular networking, small molecule annotation, and advanced MS2 interpretation within a single graphical environment. New capabilities, including interactive molecular networking, guided workflow automation, enhanced visualization, and machine learning-based spectral similarity scoring, further support exploratory and reproducible data analysis. The transition to an enterprise-supported yet open innovation model ensures long-term sustainability while preserving open-source principles. Together, these advances position mzmine 4 as a comprehensive, future-ready platform for untargeted metabolomics and mass spectrometry-based research.
读原文 · Read the paper ↗

AI 追问PRO

登录后使用 AI 追问

讨论区

登录后参与讨论

相关论文 · Related

mzmine: Unifying Mass Spectrometry Data Processing. — 科研速览 Science Skim