Journal Article


Andrew C Parnell
S. R. (Stephen R.) Pennington
Belinda Hernández



machine learning bayesian statistics liquid chromatography mass spectrometry lc ms bayesian methods development methods proteomics biomarker discovery

Bayesian methods for proteomic biomarker development (2015)

Abstract The advent of liquid chromatography mass spectrometry has seen a dramatic increase in the amount of data derived from proteomic biomarker discovery. These experiments have seemingly identified many potential candidate biomarkers. Frustratingly, very few of these candidates have been evaluated and validated sufficiently such that that they have progressed to the stage of routine clinical use. It is becoming apparent that the statistical methods used to evaluate the performance of new candidate biomarkers are a major limitation in their development. Bayesian methods offer some advantages over traditional statistical and machine learning methods. In particular they can incorporate external information into current experiments so as to guide biomarker selection. Further, they can be more robustto over-fitting than other approaches, especially when the number of samples used for discovery is relatively small. In this review we provide an introduction to Bayesian inference and demonstrate some of the advantages of using a Bayesian framework. We summarize how Bayesian methods have been used previously in proteomics and other areas of bioinformatics. Finally, we describe some popular and emerging Bayesian models from the statistical literature and provide a worked tutorial including code snippets to show how these methods may be applied for the evaluation of proteomic biomarkers.
Collections Ireland -> University College Dublin -> Conway Institute Research Collection
Ireland -> University College Dublin -> Insight Research Collection
Ireland -> University College Dublin -> Mathematics and Statistics Research Collection
Ireland -> University College Dublin -> Medicine Research Collection

Full list of authors on original publication

Andrew C Parnell, S. R. (Stephen R.) Pennington, Belinda Hernández

Experts in our system

Andrew Parnell
Maynooth University
Total Publications: 45
Stephen R Pennington
University College Dublin
Belinda Hernández
University College Dublin
Total Publications: 5