title: Identifying novel biomarkers through data mining-a realistic scenario?
abstract: In this article we discuss the requirements to use data mining of published proteomics datasets to assist proteomics-based biomarker discovery, the use of external data integration to solve the issue of inadequate small sample sizes and finally, we try to estimate the probability that new biomarkers will be identified through data mining alone.
authors.affiliation: European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK; Division of Immunology, Allergy and Infectious Diseases, Department of Dermatology, Medical University of Vienna, Austria.
authors.forename: Johannes
authors.initials: J
authors.lastname: Griss
authors.forename: Yasset
authors.initials: Y
authors.lastname: Perez-Riverol
authors.forename: Henning
authors.initials: H
authors.lastname: Hermjakob
authors.forename: Juan Antonio
authors.initials: JA
authors.lastname: Vizcaíno
mesh_terms: D015415:Biomarkers / Q000032:analysis*; D019295:Computational Biology / Q000379:methods; D057225:Data Mining / Q000379:methods*; D013058:Mass Spectrometry / Q000379:methods; D040901:Proteomics / Q000379:methods
chemical_list: D015415:Biomarkers
keywords: Bioinformatics; Biomarker; Data mining; Databases; Mass spectrometry