Knowledge-Based Analysis for Detecting Key Signaling Events from Time-Series Phosphoproteomics Data
Fig 4
The effects of completeness/accuracy of known kinase-substrate annotations on CLUE's performance.
CLUE's performance as a function of number of kinases annotated to have substrates in g out of the k clusters. The panels (from left to right) show six scenarios with true number of true simulated clusters highlighted in yellow. The scenario g = 0 resembles the situation when no existing knowledge is available for use by CLUE. CLUE's ability to accurately predict the true number of clusters improves dramatically as g increases. CLUE's performance as a function of percentage of incorrect kinase-substrate annotations (noise). We set g = 5 for testing different levels of noise (denoted as s). The panels (from left to right) show six scenarios with true number of true simulated clusters highlighted in yellow.