Chapter 10. Challenges and Research Directions in Bioinformatics and Biomarker Discovery

  1. Dr Francisco Azuaje Senior Member Associate Editor

Published Online: 14 JAN 2010

DOI: 10.1002/9780470686423.ch10

Bioinformatics and Biomarker Discovery: “Omic” Data Analysis for Personalized Medicine

Bioinformatics and Biomarker Discovery: “Omic” Data Analysis for Personalized Medicine

How to Cite

Azuaje, F. (2010) Challenges and Research Directions in Bioinformatics and Biomarker Discovery, in Bioinformatics and Biomarker Discovery: “Omic” Data Analysis for Personalized Medicine, John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470686423.ch10

Author Information

  1. Public Research Centre for Health (CRP-Santé), Luxembourg

Publication History

  1. Published Online: 14 JAN 2010
  2. Published Print: 19 FEB 2010

ISBN Information

Print ISBN: 9780470744604

Online ISBN: 9780470686423

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Keywords:

  • translational bioinformatics;
  • biomarkers;
  • education and translational bioinformatics;
  • inter-disciplinary research cooperation;
  • research training in translational research;
  • challenges in bioinformatics;
  • reporting biomarker research;
  • intelligent “omic” data analysis;
  • personalized medicine

Summary

This chapter reviews different research, technological and scientific culture challenges in translational bioinformatics and biomarker discovery. Challenges and opportunities are grouped into key areas, such as: software development, the assessment of the clinical relevance of biomarkers, and scientific cooperation. The process of evaluating and validating biomarker models is further discussed through examples of major research obstacles, success stories and computational approaches. The chapter also discusses challenges and advances in measuring and defining phenotypes. Recommendations for documenting and reporting biomarker studies are provided. This chapter assesses some of the emerging research directions in intelligent “omic” data analysis, as well as in the development of integrated biomedical computing infrastructures. Examples of problems and applications based on the exploitation of public information resources are provided. Other areas discussed in this chapter are: open access to research, systems-based approaches to biomedical knowledge discovery, and research training in translational bioinformatics