Advertisement

PanelomiX for the Combination of Biomarkers

  • Xavier RobinEmail author
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1959)

Abstract

Proteomics has allowed the discovery and validation of a massive number of biomarkers. However most of them suffer from insufficient specificity and sensitivity and therefore didn’t translate to clinical practice. Combining biomarkers with different properties into panels can be an efficient way to bypass these limitations and facilitate the translation of biomarkers into clinical practice.

Key words

Biomarkers Panel Combination of biomarkers Machine learning Clinical study 

References

  1. 1.
    Robin X, Turck N, Hainard A et al (2011) pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics 12:77. https://doi.org/10.1186/1471-2105-12-77Google Scholar
  2. 2.
    Turck N, Vutskits L, Sanchez-Pena P et al (2010) A multiparameter panel method for outcome prediction following aneurysmal subarachnoid hemorrhage. Intensive Care Med 36(1):107–115. https://doi.org/10.1007/s00134-009-1641-yGoogle Scholar
  3. 3.
    Robin X, Turck N, Hainard A et al (2013) PanelomiX: a threshold-based algorithm to create panels of biomarkers. Transl Proteom 1(1):57–64. https://doi.org/10.1016/j.trprot.2013.04.003Google Scholar
  4. 4.
    R Core Team (2018) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/. Accessed 22 Jul 2018
  5. 5.
    Breiman L (2001) Random forests. Mach Learn 45(1):5–32. https://doi.org/10.1023/A:1010933404324Google Scholar
  6. 6.
    Liaw A, Wiener M (2002) Classification and regression by randomForest. R News 2(3):18–22Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Swiss Institute of BioinformaticsUniversity of Basel, BiozentrumBaselSwitzerland

Personalised recommendations