title: Inferring the skeleton cell cycle regulatory network of malaria parasite using comparative genomic and variational Bayesian approaches.
abstract: 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.
authors.affiliation: Department of Applied Physics, University of Granada, Granada, Spain.
authors.forename: Isabel M
authors.initials: IM
authors.lastname: Tienda-Luna
authors.forename: Yufang
authors.initials: Y
authors.lastname: Yin
authors.forename: Maria C
authors.initials: MC
authors.lastname: Carrion
authors.forename: Yufei
authors.initials: Y
authors.lastname: Huang
authors.forename: Hong
authors.initials: H
authors.lastname: Cai
authors.forename: Maribel
authors.initials: M
authors.lastname: Sanchez
authors.forename: Yufeng
authors.initials: Y
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D000818:Animals; D001499:Bayes Theorem; D002453:Cell Cycle / Q000235:genetics*; D018797:Cell Cycle Proteins / Q000235:genetics / Q000378:metabolism; D003198:Computer Simulation; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D018503:Genome, Protozoan / Q000235:genetics*; D006801:Humans; D008954:Models, Biological; D020411:Oligonucleotide Array Sequence Analysis; D010963:Plasmodium falciparum / Q000166:cytology* / Q000235:genetics*; D012372:ROC Curve
chemical_list: D018797:Cell Cycle Proteins