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

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6

Proteomics and metabolomics for biomarker discovery: an introduction to spectral data analysis

This chapter will begin with an introduction to proteomics and metabolomics: Fundamental definitions, problems and key applications, with an emphasis on data obtained from spectral analysis of clinically-relevant samples. This will be followed by a discussion on the characteristics of the data and information generated in these areas, and of key approaches to biomarker discovery in proteomics and metabolomics. An introduction to feature transformation and selection will be provided, which complements the content of Chapter 3. The chapter will conclude with an overview of key computational resources and a discussion of current challenges and emerging research directions. The overview of resources will be complemented by Chapter 9.

6.1 Introduction

Proteomics and metabolomics have become promising technologies for the discovery of biomarkers in different complex multi-factorial diseases, such as cancers (Abate-Shen and Shen, 2009) and cardiovascular diseases (Sabatine et al., 2005). These areas refer to the analysis of the clinically-relevant catalogues of proteins and metabolites. These approaches may represent powerful complementary views of the molecular state of the cell at a particular time. One of the major challenges is the diversity of cell types contributing to the human proteome and metabolome (e.g. measured in the plasma) and the low concentration levels of many of the proteins ...

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