Output details
13 - Electrical and Electronic Engineering, Metallurgy and Materials
University of Birmingham : A - Electronic, Electrical and computer engineering
A Signal Filtering Method for Improved Quantification and Noise Discrimination in Fourier Transform Ion Cyclotron Resonance Mass Spectrometry-Based Metabolomics Data
The long-standing challenge of accurate signal quantification and discrimination of real signals from noise in fourier transform ion cyclotron resonance mass spectrometry is addressed. Building on original Birmingham SIM-stitching technology, and widely used in the community (evidenced by international citations), the novelty of the method lies in a unique three-stage filtering approach for substantially improving signal-to-noise characteristics of the data. The paper provides a complete experimental analysis on the benefits of the filtering approach compared to current methods. The approach is validated in collaboration with the Centre for Environment, Fisheries, and Aquaculture, looking at liver tissue from flatfish.
