Article ; Online: Accurate Prediction of Ion Mobility Collision Cross-Section Using Ion's Polarizability and Molecular Mass with Limited Data.
Journal of chemical information and modeling
2024 Volume 64, Issue 5, Page(s) 1533–1542
Abstract: The rotationally averaged collision cross-section (CCS) determined by ion mobility-mass spectrometry (IM-MS) facilitates the identification of various biomolecules. Although machine learning (ML) models have recently emerged as a highly accurate approach ...
Abstract | The rotationally averaged collision cross-section (CCS) determined by ion mobility-mass spectrometry (IM-MS) facilitates the identification of various biomolecules. Although machine learning (ML) models have recently emerged as a highly accurate approach for predicting CCS values, they rely on large data sets from various instruments, calibrants, and setups, which can introduce additional errors. In this study, we identified and validated that ion's polarizability and mass-to-charge ratio ( |
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MeSH term(s) | Ions/chemistry ; Ion Mobility Spectrometry/methods |
Chemical Substances | Ions |
Language | English |
Publishing date | 2024-02-23 |
Publishing country | United States |
Document type | Journal Article |
ZDB-ID | 190019-5 |
ISSN | 1549-960X ; 0095-2338 |
ISSN (online) | 1549-960X |
ISSN | 0095-2338 |
DOI | 10.1021/acs.jcim.3c01491 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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