Related Experiment Video
Updated: Feb 12, 2026

Quantitative Metabolomics of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry
Published on: January 5, 2021
KniMet: a pipeline for the processing of chromatography-mass spectrometry metabolomics data
Sonia Liggi1, Christine Hinz2, Zoe Hall2
1Department of Biochemistry and Cambridge Systems Biology Centre, University of Cambridge, Cambridge, UK. sl584@cam.ac.uk.
Introduction:
Data processing is one of the biggest problems in metabolomics, given the high number of samples analyzed and the need of multiple software packages for each step of the processing workflow.
Objectives:
Merge in the same platform the steps required for metabolomics data processing.
Methods:
KniMet is a workflow for the processing of mass spectrometry-metabolomics data based on the KNIME Analytics platform.
Results:
The approach includes key steps to follow in metabolomics data processing: feature filtering, missing value imputation, normalization, batch correction and annotation.
Conclusion:
KniMet provides the user with a local, modular and customizable workflow for the processing of both GC-MS and LC-MS open profiling data.
More Related Videos
Related Concept Videos
Gas Chromatography–Mass Spectrometry (GC–MS)
A gas chromatograph consists of a long, narrow capillary column with a polysiloxane coating on the inner wall....
Mass Spectrometry: Overview
Tandem Mass Spectrometry
Mass Spectrometry of Amines
Mass Spectrometry: Isotope Effect
Chemical Ionization (CI) Mass Spectrometry

