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Updated: Feb 27, 2026

Using a Cyclic Ion Mobility Spectrometer for Tandem Ion Mobility Experiments

Using a Cyclic Ion Mobility Spectrometer for Tandem Ion Mobility Experiments

Published on: January 20, 2022

高次元イオン移動度データの可逆ジャンプマルコフ連鎖モンテカルロ法によるデコンボリューション

Jerome Riedel^1,2, Marc Safferthal^1,2, Gergo Peter Szekeres^1,2

¹Freie Universität Berlin, Altensteinstraße 23A, Berlin 14195, Germany.

Analytical chemistry

|February 26, 2026

Abstract:

Deconvolution of multicomponent arrival time distributions is known to be a highly challenging task due to the "curse of dimensionality". Therefore, the development of a robust global optimizer is a crucial milestone in the automated analysis of arrival time distributions for collision cross section extraction and population analysis. Here, we report an approach that combines gas-phase ion transport theory with equi-energy sampling, Bayesian sequential partitioning, and reversible-jump Markov chain Monte Carlo to automatically determine probabilities of deconvolution solutions and predict the number of components in the arrival time distribution. The robustness of the method was evaluated against synthetic and experimental drift tube ion mobility data to find global deconvolution solutions and automatically determine collision cross sections. Analyzing the collision-induced unfolding profile of cytochrome c using the developed pipeline ultimately enables tracking of the conformational ensemble under activation. Additionally, using the same strategy on isomeric O-glycan species further revealed the potential for cross-platform collision cross section annotations.

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Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules

Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules

Published on: September 5, 2019

T-wave Ion Mobility-mass Spectrometry: Basic Experimental Procedures for Protein Complex Analysis

T-wave Ion Mobility-mass Spectrometry: Basic Experimental Procedures for Protein Complex Analysis

Published on: July 31, 2010

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