This book is designed to introduce biologists, clinicians andcomputational researchers to fundamental data analysis principles,techniques and tools for supporting the discovery of biomarkers andthe implementation of diagnostic/prognostic systems.The focus of the book is on how fundamental statistical and datamining approaches can support biomarker discovery and evaluation,emphasising applications based on different types of "omic" data.The book also discusses design factors, requirements and techniquesfor disease screening, diagnostic and prognostic applications.Readers are provided with the knowledge needed to assess therequirements, computational approaches and outputs in diseasebiomarker research. Commentaries from guest experts are alsoincluded, containing detailed discussions of methodologies andapplications based on specific types of "omic" data, as well astheir integration. Covers the main range of data sources currentlyused for biomarker discovery* Covers the main range of data sources currently used forbiomarker discovery* Puts emphasis on concepts, design principles and methodologiesthat can be extended or tailored to more specific applications* Offers principles and methods for assessing thebioinformatic/biostatistic limitations, strengths and challenges inbiomarker discovery studies* Discusses systems biology approaches and applications* Includes expert chapter commentaries to further discussrelevance of techniques, summarize biological/clinical implicationsand provide alternative interpretations