No document available.
Keywords :
chemometrics; classification; machine learning; mass spectrometry; regression; Basic principles; Chemometrices; Comprehensive two-dimensional gas chromatography; Data alignments; Data processing techniques; GC×GC; Machine-learning; Regression; Research applications; Statistical approach; Chemistry (all); Biochemistry, Genetics and Molecular Biology (all)
Abstract :
[en] This chapter explains how raw data from gas chromatography coupled with mass spectrometry (GC-MS) and comprehensive two-dimensional gas chromatography coupled with mass spectrometry (GC×GC-MS) are structured. Also, it outlines the data processing techniques used to extract meaningful information. It introduces the basic principles of commonly employed statistical approaches, such as chemometrics and machine learning, in the field of GC(×GC)-MS. Choosing and evaluating the most appropriate strategy is essential for a wide range of targeted and untargeted research applications, including data alignment, feature selection, and longitudinal or cross-sectional studies.
Disciplines :
Physical, chemical, mathematical & earth Sciences: Multidisciplinary, general & others
dos Santos, Allyson L. R.; Instituto de Química, Universidade Estadual de Campinas, Campinas, Brazil ; Instituto Nacional de Ciência e Tecnologia em Bioanalítica, Universidade Estadual de Campinas, Campinas, Brazil
Hantao, Leandro W.; Instituto de Química, Universidade Estadual de Campinas, Campinas, Brazil ; Instituto Nacional de Ciência e Tecnologia em Bioanalítica, Universidade Estadual de Campinas, Campinas, Brazil
Scopus citations®
without self-citations
0