Computational Biology Commons^™

Prediction Of Kinase-Substrate Associations Using The Functional Landscape Of Kinases And Phosphorylation Sites, Serhan Yilmaz, Filipa Blasco Tavares Pereira Lopes, Mark R. Chance, Mehmet Koyutürk

Faculty Scholarship

Protein phosphorylation is a key post-translational modification that plays a central role in many cellular processes. With recent advances in biotechnology, thousands of phosphorylated sites can be identified and quantified in a given sample, enabling proteome-wide screening of cellular signaling. However, for most (> 90%) of the phosphorylation sites that are identified in these experiments, the kinase(s) that target these sites are unknown. To broadly utilize available structural, functional, evolutionary, and contextual information in predicting kinase-substrate associations (KSAs), we develop a network-based machine learning framework. Our framework integrates a multitude of data sources to characterize the landscape of functional relationships …