title: Data Fusion in Metabolomics and Proteomics for Biomarker Discovery.
abstract: Proteomics and metabolomics provide key insights into status and dynamics of biological systems. These molecular studies reveal the complex mechanisms involved in disease or aging processes. Invaluable information can be obtained using various analytical techniques such as nuclear magnetic resonance, liquid chromatography, or gas chromatography coupled to mass spectrometry. Each method has inherent advantages and drawbacks, but they are complementary in terms of biological information.The fusion of different measurements is a complex topic. We describe here a framework allowing combining multiple data sets, provided by different analytical platforms. For each platform, the relevant information is extracted in the first step. The obtained latent variables are then fused and further analyzed. The influence of the original variables is then calculated back and interpreted.
authors.affiliation: Analytical Chemistry-Chemometrics, Institute for Molecules and Materials, Radboud University Nijmegen, Heyendaalseweg 135, 6525 AJ, Nijmegen, The Netherlands. l.blanchet@science.ru.nl.|Department of Biochemistry, Nijmegen Centre for Molecular Life Sciences, Radboud University Medical Centre, Geert Grooteplein 10, Nijmegen, The Netherlands. l.blanchet@science.ru.nl.
authors.forename: Lionel
authors.initials: L
authors.lastname: Blanchet
authors.affiliation: Department of Toxicology, Nutrition and Toxicology Research Institute Maastricht (NUTRIM), Maastricht University, Maastricht, The Netherlands.
authors.forename: Agnieszka
authors.initials: A
authors.lastname: Smolinska
mesh_terms: D015415:Biomarkers; D055432:Metabolomics / Q000379:methods*; D015233:Models, Statistical; D040901:Proteomics / Q000379:methods*
chemical_list: D015415:Biomarkers
keywords: Chemometrics; Discriminant analysis; Latent variable; PLS-DA; Variable selection; eCVA