Fusion of metabolomics and proteomics data for biomarkers discovery: case study on the experimental autoimmune encephalomyelitis

Background: Analysis of Cerebrospinal Fluid (CSF) samples holds great promise to diagnose neurological pathologies and gain insight into the molecular background of these pathologies. Proteomics and metabolomics methods provide invaluable information on the biomolecular content of CSF and thereby on the possible status of the central nervous system, including neurological pathologies. The combined information provides a more complete description of CSF content. Extracting the full combined information requires a combined analysis of different datasets i.e. fusion of the data. Results: A novel fusion method is presented and applied to proteomics and metabolomics data from a pre-clinical model of multiple sclerosis: an Experimental Autoimmune Encephalomyelitis (EAE) model in rats. The method follows a mid-level fusion architecture. The relevant information is extracted per platform using extended canonical variates analysis. The results are subsequently merged in order to be analyzed jo...

• Type: Journal
• Year: 2011
• Where: BMCBI
• Authors: Lionel Blanchet, Agnieszka Smolinska, Amos Attali, Marcel P. Stoop, Kirsten A. M. Ampt, Hans van Aken, Ernst Suidgeest, Tinka Tuinstra, Sybren S. Wijmenga, Theo Luider, Lutgarde M. C. Buydens
• Keywords: Biological Pathways, Biometrics, BMCBI 2011, Fusion Approach, Fusion Method