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Bioinformatics and Biomarker Discovery: "Omic" Data Analysis for Personalized Medicine by Francisco Azuaje

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Biomarkers and bioinformatics

This chapter discusses key concepts, problems and research directions. It provides an introduction to translational biomedical research, personalized medicine, and biomarkers: types and main applications. It will introduce fundamental data types, computational and statistical requirements in biomarker studies, an overview of recent advances, and a comparison between ‘traditional’ and ‘novel’ molecular biomarkers. Significant roles of bioinformatics in biomarker research will be illustrated, as well as examples of domain-specific models and applications. It will end with a summary of expected learning outcomes, content overview, and a description of basic mathematical notation to be used in the book.

1.1 Bioinformatics, translational research and personalized medicine

In this book, the term bioinformatics refers to the design, implementation and application of computational technologies, methods and tools for making ‘omic’ data meaningful. This involves the development of information and software resources to support a more open and integrated access to data and information. Bioinformatics is also used in the context of emerging computational technologies for modelling complex systems and informational patterns for predictive purposes. This book is about the discovery of knowledge from human molecular and clinical data through bioinformatics. Knowledge that represents ‘biomarkers’ of disease and clinically-relevant phenotypes.

Another key issue that ...

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