Computational tools and algorithms for ion mobility spectrometry-mass spectrometry.
Dylan H RossHarsh BhotikaXueyun ZhengRichard D SmithKristin E Burnum-JohnsonAivett BilbaoPublished in: Proteomics (2024)
Ion mobility spectrometry-mass spectrometry (IMS-MS or IM-MS) is a powerful analytical technique that combines the gas-phase separation capabilities of IM with the identification and quantification capabilities of MS. IM-MS can differentiate molecules with indistinguishable masses but different structures (e.g., isomers, isobars, molecular classes, and contaminant ions). The importance of this analytical technique is reflected by a staged increase in the number of applications for molecular characterization across a variety of fields, from different MS-based omics (proteomics, metabolomics, lipidomics, etc.) to the structural characterization of glycans, organic matter, proteins, and macromolecular complexes. With the increasing application of IM-MS there is a pressing need for effective and accessible computational tools. This article presents an overview of the most recent free and open-source software tools specifically tailored for the analysis and interpretation of data derived from IM-MS instrumentation. This review enumerates these tools and outlines their main algorithmic approaches, while highlighting representative applications across different fields. Finally, a discussion of current limitations and expectable improvements is presented.
Keyphrases
- mass spectrometry
- liquid chromatography
- gas chromatography
- high resolution
- high performance liquid chromatography
- capillary electrophoresis
- multiple sclerosis
- ms ms
- tandem mass spectrometry
- machine learning
- organic matter
- magnetic resonance imaging
- deep learning
- smoking cessation
- big data
- single cell
- artificial intelligence
- label free