Predicting novel interactionsIn situ proximity ligation assay confirmed the prediction of a novel interaction between EGFR and PDLIM1coOcc_cropPhosphotyrosine interacting with an SH2 domainprettyProteomeScout is our database of proteins and post-translational modifications.noiseModel

Predicting transient protein interactions driven by phosphorylation using unsupervised learning and graph theory.

In situ proximity ligation assay confirmed the prediction of a novel interaction between EGFR and PDLIM1

The co-occurrence matrix is a way to measure the robustness of clustering of objects across ensembles of clustering solutions.

Phosphotyrosine interacting with an SH2 domain

The Naegle lab uses molecular and cellular techniques to test hypotheses.

ProteomeScout is our database of proteins and post-translational modifications.

The Naegle lab proposed a model for sampling new data, even with few replicates, by building noise models from similar systems.

The Naegle lab seeks to understand the regulation and function of tyrosine phosphorylation in complex networks.

Tyrosine phosphorylation is a protein modification that can occur during or after translation of a protein.The phosphate addition to a tyrosine residue, regulated by tyrosine kinases and phosphatases, can result in changes in protein function, regulation and localization. It is key to important cell signaling processes, which are the processes that convert extracellular cues, like growth factors and insulin, into biochemical networks that result in a change to the cell.  Tyrosine phosphorylation is specifically utilized in the early events of receptor tyrosine kinase (RTK) networks, which are fundamental to many processes in the development and homeostasis of complex organisms.  Improvements in measurement technologies have enabled the ability to detect and monitor tyrosine phosphorylation and now we know that tyrosine phosphorylation is extensive — occurring on thousands of tyrosines in the human proteome.

Given the sheer size of the challenge, we use both computational and molecular technologies to predict and test the role of tyrosine phosphorylation on proteins and in cellular networks.  Although we incorporate new mathematical and computational methods as needed to tackle the fundamental problems of our research, those techniques always have a foundation in statistical robustness. Hypotheses are tested in molecular and cellular systems, closing the loop between computation and experimentation.

The questions that drive us include:

  • How do we increase the capabilities of research to gain new understanding of tyrosine phosphorylation rapidly, i.e. in a high-throughput manner that matches the rate of discovery of these modifications?
  • How do we develop new capabilities to understand how these networks act in specific contexts? Cell context refers to the differences we see between tissue types and the states of the network components that lead to differential responses of tissues to the same cue. As a philosophy, we approach network dysregulation that occurs in disease as an alteration in cell context.