, Volume 132, Issue 2, pp 131–142 | Cite as

Inferring the skeleton cell cycle regulatory network of malaria parasite using comparative genomic and variational Bayesian approaches

  • Isabel M. Tienda-Luna
  • Yufang Yin
  • Maria C. Carrion
  • Yufei Huang
  • Hong Cai
  • Maribel Sanchez
  • Yufeng Wang


The development of new antimalarial drugs is urgently needed due to elevated drug resistance in the causative agents Plasmodium parasites. An intervention strategy based on the interruption of the parasite cell cycle could be undertaken using a systems-biology aided drug discovery approach. However, little is known about the components or the mechanism of parasite cell cycle control to date. In this proof of concept study, we attempted to infer the skeleton components using comparative genomic analysis and to uncover the genetic regulatory network (GRN) ab initio using a Variational Bayesian expectation maximization (VBEM) approach.


Cell cycle Genetic regulatory network Malaria Plasmodium Variational Bayesian 



a posteriori probability


Area under the curve


Basic local alignment search tool


Genetic regulatory network


Kyoto encyclopedia of genes and genomes


Maximum a posteriori


Mitogen-activated protein kinase


Minichromosome maintenance


Open reading frame


Proliferating cell nuclear antigen


Receiver operating characteristic


Variational Bayesian expectation maximization


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Copyright information

© Springer Science+Business Media B.V. 2007

Authors and Affiliations

  • Isabel M. Tienda-Luna
    • 1
  • Yufang Yin
    • 2
  • Maria C. Carrion
    • 1
  • Yufei Huang
    • 2
  • Hong Cai
    • 2
  • Maribel Sanchez
    • 3
  • Yufeng Wang
    • 3
  1. 1.Department of Applied PhysicsUniversity of GranadaGranadaSpain
  2. 2.Department of Electrical and Computer EngineeringUniversity of Texas at San AntonioSan AntonioUSA
  3. 3.Department of BiologyUniversity of Texas at San AntonioSan AntonioUSA

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