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KODAMA exploratory analysis in metabolic phenotyping

Article scientifique 2023 Anglais

Résumé

KODAMA is a valuable tool in metabolomics research to perform exploratory analysis. The advanced analytical technologies commonly used for metabolic phenotyping, mass spectrometry, and nuclear magnetic resonance spectroscopy push out a bunch of high-dimensional data. These complex datasets necessitate tailored statistical analysis able to highlight potentially interesting patterns from a noisy background. Hence, the visualization of metabolomics data for exploratory analysis revolves around dimensionality reduction. KODAMA excels at revealing local structures in high-dimensional data, such as metabolomics data. KODAMA has a high capacity to detect different underlying relationships in experimental datasets and correlate extracted features with accompanying metadata. Here, we describe the main application of KODAMA exploratory analysis in metabolomics research.

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Zinga, M., Abdel-Shafy, E., Melak, T., Vignoli, A., Piazza, S., Zerbini, L., Tenori, L., Cacciatore, S. (2023). KODAMA exploratory analysis in metabolic phenotyping. https://doi.org/10.3389/fmolb.2022.1070394

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Auteur(s)

Maria Zinga Ebtesam A. Abdel-Shafy Tadele Melak Alessia Vignoli Silvano Piazza Luiz F. Zerbini Leonardo Tenori Stefano Cacciatore

Statistiques

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