Читать книгу Multiblock Data Fusion in Statistics and Machine Learning - Tormod Næs - Страница 25

Biomarkers:Chemical compounds (e.g., metabolites) that mark a difference between conditions, e.g., between healthy and diseased persons.GC-MS:Gas chromatography–mass spectrometry. A separation method coupled to a mass spectrometer used a lot in advanced chemical analyses of volatile compounds.LC-MS:Liquid chromatography–mass spectrometry. A separation method coupled to a mass spectrometer used a lot in advanced chemical analyses for a large diversity of chemical compounds.Metabolome:The set of all metabolites of a biological organism responsible for its metabolism.NMR:Nuclear magnetic resonance. A fast chemical analysis method giving a fingerprint of a sample and concentrations of chemical compounds.Proteomics:The study and measurements of proteins in biological organisms. Proteins are mostly enzymes catalysing metabolic reactions.

There are several multiblock data analysis challenges in metabolomics. It is increasingly popular to measure different sets of chemically related metabolites on the same samples using different instrumental protocols (Smilde et al., 2005b; Pellis et al., 2012; Kardinaal et al., 2015). These blocks of data (each block pertaining to one instrumental protocol) then need to be combined to arrive at a global view on metabolism. Metabolites can also be measured in different compartments, such as in blood, urine, liver, muscle, kidney (Fazelzadeh et al., 2016). This also generates multiblock data analysis problems. Metabolites are converted in biochemical reactions catalysed by enzymes (proteins). Hence, it is also worthwhile in some cases to measure proteins and combine those with metabolomics measurements (Wopereis et al., 2009). Plants are complex organisms with a rich variety of metabolites. The metabolism of plants is influenced by environmental conditions, such as temperature and light. Example 1.1 illustrates this.