Reconstructing Boolean Models of Signaling

  • Roded Sharan
  • Richard M. Karp
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7262)


Since the first emergence of protein-protein interaction networks, more than a decade ago, they have been viewed as static scaffolds of the signaling-regulatory events taking place in the cell and their analysis has been mainly confined to topological aspects. Recently, functional models of these networks have been suggested, ranging from Boolean to constraint-based ones. However, learning such models from large-scale data remains a formidable task and most modeling approaches rely on extensive human curation. Here we provide a generic approach to learning Boolean models automatically from data. We apply our approach to growth and inflammatory signaling systems in human and show how the learning phase can improve the fit of the model to experimental data, remove spurious interactions and lead to better understanding of the system at hand.


Signaling network Boolean modeling Integer linear programming 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Roded Sharan
    • 1
  • Richard M. Karp
    • 2
  1. 1.Blavatnik School of Computer ScienceTel Aviv UniversityTel AvivIsrael
  2. 2.International Computer Science InstituteBerkeleyUSA

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