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Opportunities and Challenges of Multiplex Assays: A Machine Learning Perspective

  • Junfang Chen
  • Emanuel SchwarzEmail author
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1546)

Abstract

Multiplex assays that allow the simultaneous measurement of multiple analytes in small sample quantities have developed into a widely used technology. Their implementation spans across multiple assay systems and can provide readouts of similar quality as the respective single-plex measures, albeit at far higher throughput. Multiplex assay systems are therefore an important element for biomarker discovery and development strategies but analysis of the derived data can face substantial challenges that may limit the possibility of identifying meaningful biological markers. This chapter gives an overview of opportunities and challenges of multiplexed biomarker analysis, in particular from the perspective of machine learning aimed at identification of predictive biological signatures.

Key words

Biomarker discovery Machine learning Confounding Bias Multiplex 

Notes

Acknowledgments

This study was supported by the DFG Emmy-Noether-Program SCHW 1768/1-1.

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Copyright information

© Springer Science+Business Media LLC 2017

Authors and Affiliations

  1. 1.Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty MannheimHeidelberg UniversityMannheimGermany

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