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KODAMA exploratory analysis in metabolic phenotyping

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 necessita...

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Detalles Bibliográficos
Autores principales: Zinga, Maria Mgella, Abdel-Shafy, Ebtesam, Melak, Tadele, Vignoli, Alessia, Piazza, Silvano, Zerbini, Luiz Fernando, Tenori, Leonardo, Cacciatore, Stefano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9887019/
https://www.ncbi.nlm.nih.gov/pubmed/36733493
http://dx.doi.org/10.3389/fmolb.2022.1070394
Descripción
Sumario: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.