Sisco, E.
(2022),
Algorithms and databases: unlocking non-targeted screening of small molecules with ambient ionization mass spectrometry, LCGC North America, [online], https://doi.org/10.56530/lcgc.na.xm8779p2, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=935329, https://www.chromatographyonline.com/view/algorithms-and-databases-unlocking-non-targeted-screening-of-small-molecules-with-ambient-ionization-mass-spectrometry
(Accessed April 16, 2024)
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Algorithms and databases: unlocking non-targeted screening of small molecules with ambient ionization mass spectrometry
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Abstract
Nearly all sectors of analytical chemistry are finding applications for ambient ionization mass spectrometry (AI-MS) due to its ease of use, speed of analysis and sensitivity. While emphasis has been placed on developing new hardware to help analyze unique samples across various applications, there has not been much innovation in the way of software tools and mass spectral libraries to support applications like non-targeted searching. In this article, we discuss new algorithms and libraries that have enabled non-targeted analysis of small molecules using AI-MS, as well as some of the key considerations and outstanding questions in the field.Citation
LCGC North America
Volume
40
Pub Type
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Created September 1, 2022, Updated December 19, 2022