CHICKN: extraction of peptide chromatographic elution profiles from large scale mass spectrometry data by means of Wasserstein compressive hierarchical cluster analysis

CHICKN: extraction of peptide chromatographic elution profiles from large scale mass spectrometry data by means of Wasserstein compressive hierarchical cluster analysis

Background: The clustering of data produced by liquid chromatography coupled to mass spectrometry analyses (LC-MS data) has recently gained interest to extract meaningful chemical or biological patterns. However, recent instrumental pipelines deliver data which size, dimensionality and expected numb...

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Bibliographic Details
Main Authors: Burger, T. (Author), Fortin, T. (Author), Guibert, R. (Author), Hesse, A.-M (Author), Kraut, A. (Author), Permiakova, O. (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
algorithm
Algorithms
chemistry
Chromatography, Liquid
cluster analysis
Cluster Analysis
Data Compression
Data mining
Data representations
Essential features
Hierarchical clustering
Hierarchical strategies
Hierarchical systems
information processing
K-means clustering
Large-scale cluster analysis
Learning algorithms
liquid chromatography
Liquid chromatography
Machine learning
mass spectrometry
Mass spectrometry
Mass Spectrometry
Mass spectrometry analysis
Mass spectrometry data
Multi-core machines
Objective functions
Optimal transport
peptide
Peptides
procedures
proteomics
Proteomics
State-of-the-art methods
Wasserstein kernel
Online Access:View Fulltext in Publisher

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