Overcoming bias in phosphoproteomics
21 Oct 2011
Phosphorylation, i.e. adding a phosphate group to proteins, is a key step in numerous biological processes and pathways. Insight into the functional dynamics of phosphorylation networks is essential to understand how a living cell operates. Studying the phosphoproteome - all proteins involved in phosphorylation - has recently gained an enormous boost. But comparing and integrating data on phosphoproteomes is complicated due to incomplete datasets and to biases caused by the use of different experimental workflows. Jos Boekhorst (Utrecht University) and colleagues have developed bioinformatics strategies to quantify the impact of different experimental workflows on measured phosphoproteomes by comparing datasets to a common reference. Their strategies also offer possibilities for extracting information through comparative analysis of available phosphorylation data from sources not specifically generated for phosphoproteome studies.
Evaluating experimental bias and incompleteness in comparative phosphoproteomics analysis
Boekhorst J, Boersema PJ, Tops BB, van Breukelen B, Heck AJ and Snel B