title: Network-Assisted Disease Classification and Biomarker Discovery.
abstract: Developing improved approaches for diagnosis, treatment, and prevention of diseases is a major goal of biomedical research. Therefore, the discovery of biomarker signatures from high-throughput "omics" data is an active research topic in the field of bioinformatics and systems medicine. A major issue is the low reproducibility and the limited biological interpretability of candidate biomarker signatures identified from high-throughput data. This impedes the use of discovered biomarker signatures into clinical applications. Currently, much focus is placed on developing strategies to improve reproducibility and interpretability. Researchers have fruitfully started to incorporate prior knowledge derived from pathways and molecular networks into the process of biomarker identification. In this chapter, after giving a general introduction to the problem of disease classification and biomarker discovery, we will review two types of network-assisted approaches: (1) approaches inferring activity scores for specific pathways which are subsequently used for classification and (2) approaches identifying subnetworks or modules of molecular networks by differential network analysis which can serve as biomarker signatures.
authors.affiliation: Biomathematics and Bioinformatics Unit, Leibniz-Institute for Farm Animal Biology (FBN), Institute of Genetics and Biometry, Wilhelm-Stahl-Allee 2, Dummerstorf, 18196, Germany.
authors.forename: Sonja
authors.initials: S
authors.lastname: Strunz
authors.affiliation: Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, Germany.|Stellenbosch Institute for Advanced Study (STIAS), Wallenberg Research Centre at Stellenbosch University, Stellenbosch, South Africa.
authors.forename: Olaf
authors.initials: O
authors.lastname: Wolkenhauer
authors.affiliation: Biomathematics and Bioinformatics Unit, Leibniz-Institute for Farm Animal Biology (FBN), Institute of Genetics and Biometry, Wilhelm-Stahl-Allee 2, Dummerstorf, 18196, Germany. fuente@fbn-dummerstorf.de.
authors.forename: Alberto
authors.initials: A
authors.lastname: de la Fuente
mesh_terms: D015415:Biomarkers; D019295:Computational Biology / Q000379:methods; D020000:Decision Support Systems, Clinical; D053263:Gene Regulatory Networks; D006801:Humans; D008954:Models, Biological; D060066:Protein Interaction Maps; D015398:Signal Transduction
chemical_list: D015415:Biomarkers
keywords: Biomarker discovery; Classification; Feature selection; Molecular networks; Pathways