Validation of Gene Regulatory Networks from Protein-Protein Interaction Data: Application to Cell-Cycle Regulation

  • Iti Chaturvedi
  • Meena Kishore Sakharkar
  • Jagath C. Rajapakse
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4774)


We develop a technique to validate large-scale gene regulatory networks (GRN) by comparing with corresponding protein-protein interaction (PPI) networks. The GRN are obtained with Bayesian networks while PPI networks are obtained from database of known PPI interactions. We look for exact matches and then reduced networks by skipping one or more genes in GRN. We demonstrate our technique on expression profiles of differentially expressed genes in the S. cerevisiae cell cycle. We validate GRNs against a merged database of 53235 genes. The precisions of GRN obtained over all genes were from 0.82 to 0.95 in all the phases. In particular we realized that one-skip and two-skip model significantly improved accuracy of the GRN of different phases of cell cycle.


Dynamic Bayesian networks gene regulatory networks genetic algorithms protein-protein interactions 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Iti Chaturvedi
    • 1
    • 2
  • Meena Kishore Sakharkar
    • 2
  • Jagath C. Rajapakse
    • 1
  1. 1.Bioinformatics Research Center, Nanyang Technological UniversitySingapore
  2. 2.Adams Lab, MAE, Nanyang Technological UniversitySingapore

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