Reconstruction of Protein Networks Using Reverse-Phase Protein Array Data

Part of the Methods in Molecular Biology book series (MIMB, volume 1362)


In this chapter, we describe an approach to reconstruct cellular signaling networks based on measurements of protein activation after different stimulation experiments. As experimental platform reverse-phase protein arrays (RPPA) are used. RPPA allow the measurement of proteins and phosphoproteins across many samples in parallel with minimal sample consumption using a panel of highly target protein-specific antibodies. Functional interactions of proteins are modeled using a Boolean network. We describe the Boolean network reconstruction approach ddepn (dynamic deterministic effects propagation networks), which uses time course data to derive protein interactions based on perturbation experiments. We explain how the method works, give a practical application example, and describe how the results can be interpreted. Furthermore prior knowledge on signaling pathways is essential for network reconstruction. Here we describe the use of our software rBiopaxParser to integrate prior knowledge on protein signaling available in public databases. All applied methods are freely available as open-source R software packages. We describe the preparation of RPPA data as well as all relevant programming steps to format the RPPA data, to infer the prior knowledge, and to reconstruct and analyze the protein signaling networks.

Key words

Reverse-phase protein arrays Proteomics Protein signaling DDEPN Network reconstruction Boolean modeling 


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of Medical StatisticsUniversity Medical Center GöttingenGöttingenGermany
  2. 2.IndivuTest GmbHHamburgGermany
  3. 3.Division of Molecular Genome AnalysisGerman Cancer Research Center (DKFZ)HeidelbergGermany
  4. 4.TRON-Translational Oncology at the University Medical Center MainzMainzGermany

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