Inversion of a nano-Liquid Chromatography dynamical model for quantitative proteomics

This paper presents an adaptive method which enables estimation of protein quantity present in complex mixtures (urine, plasma) analyzed by an LC-MS (Liquid Chromatography and Mass Spectrometry) system. The proposed approach is based on the inversion of a parametric state space model describing the chromatographic column behaviour. Efficiency of the algorithm is tested on synthetic and real dataset