title: Combining metabonomics and other -omics data.
abstract: Combining molecular profiling data from multiple -omics platforms has the potential to provide a more comprehensive characterization of the biological system as well as improved prediction models for diagnostic applications compared to information derived from a single molecular profiling platform. In this chapter we outline analysis strategies for characterization of the genetic drivers of metabolism, joint pathway analysis in metabonomic and transcriptomic data and how metabonomic, and other -omics data can be combined to improve prediction models.
authors: Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 281, Stockholm, SE-171 77, Sweden, mattias.rantalainen@ki.se.
authors: Mattias
authors: M
authors: Rantalainen
mesh_terms: D006801:Humans; D055432:Metabolomics / Q000379:methods*; D040901:Proteomics; D040641:Quantitative Trait Loci / Q000235:genetics; D019655:Quantitative Trait, Heritable; D012372:ROC Curve; D015398:Signal Transduction; D013223:Statistics as Topic; D059467:Transcriptome