title: Gene regulatory networks and their applications: understanding biological and medical problems in terms of networks.
abstract: In recent years gene regulatory networks (GRNs) have attracted a lot of interest and many methods have been introduced for their statistical inference from gene expression data. However, despite their popularity, GRNs are widely misunderstood. For this reason, we provide in this paper a general discussion and perspective of gene regulatory networks. Specifically, we discuss their meaning, the consistency among different network inference methods, ensemble methods, the assessment of GRNs, the estimated number of existing GRNs and their usage in different application domains. Furthermore, we discuss open questions and necessary steps in order to utilize gene regulatory networks in a clinical context and for personalized medicine.
authors.affiliation: Computational Biology and Machine Learning Laboratory, Faculty of Medicine, Health and Life Sciences, Center for Cancer Research and Cell Biology, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast Belfast, UK.
authors.forename: Frank
authors.initials: F
authors.lastname: Emmert-Streib
authors.affiliation: Institute for Bioinformatics and Translational Research, UMIT Hall in Tyrol, Austria.
authors.forename: Matthias
authors.initials: M
authors.lastname: Dehmer
authors.affiliation: Bioinformatics and Computational Genomics Laboratory, Department of Medical Biophysics, Princess Margaret Cancer Centre, University of Toronto Canada.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Haibe-Kains
keywords: biomarker; computational genomics; gene regulatory networks; network analysis; personalized medicine; statistical inference; systems biology