title: Efficient computation of minimal perturbation sets in gene regulatory networks.
abstract: In the last few decades, technological and experimental advancements have enabled a more precise understanding of the mode of action of drugs with respect to human cell signaling pathways and have positively influenced the design of new drug compounds. However, as the design of compounds has become increasingly target-specific, the overall effects of a drug on adjacent cellular signaling pathways remain difficult to predict because of the complexity of the interactions involved. Off-target effects of drugs are known to influence their efficacy and safety. Similarly, drugs which are more target-specific also suffer from lack of efficacy because their scope might be too limited in the context of cellular signaling. Even in situations where the signaling pathways targeted by a drug are known, the presence of point mutations in some of the components of the pathways can render a therapy ineffective in a considerable target subpopulation. Some of these issues can be addressed by predicting Minimal Intervention Sets (MIS) of elements of the signaling pathways that when perturbed give rise to a pre-defined cellular phenotype. These minimal gene perturbation sets can then be further used to screen a library of drug compounds in order to discover effective drug therapies. This manuscript describes algorithms that can be used to discover MIS in a gene regulatory network that can lead to a defined cellular phenotype. Algorithms are implemented in our Boolean modeling toolbox, GenYsis. The software binaries of GenYsis are available for download from http://www.vital-it.ch/software/genYsis/.
authors.affiliation: Vital-IT Systems Biology Division, SIB Swiss Institute of Bioinformatics Lausanne, Switzerland.
authors.forename: Abhishek
authors.initials: A
authors.lastname: Garg
authors.affiliation: Electrical and Computer Engineering, University of Pittsburgh Pittsburgh, PA, USA.
authors.forename: Kartik
authors.initials: K
authors.lastname: Mohanram
authors.affiliation: Quartz Bio Plan-Les-Ouates, Switzerland.
authors.forename: Alessandro
authors.initials: A
authors.lastname: Di Cara
authors.affiliation: Center for Integrative Genomics, University of Lausanne Lausanne, Switzerland.
authors.forename: Gwendoline
authors.initials: G
authors.lastname: Degueurce
authors.affiliation: Vital-IT Systems Biology Division, SIB Swiss Institute of Bioinformatics Lausanne, Switzerland.
authors.forename: Mark
authors.initials: M
authors.lastname: Ibberson
authors.affiliation: Vital-IT Systems Biology Division, SIB Swiss Institute of Bioinformatics Lausanne, Switzerland.
authors.forename: Julien
authors.initials: J
authors.lastname: Dorier
authors.affiliation: Vital-IT Systems Biology Division, SIB Swiss Institute of Bioinformatics Lausanne, Switzerland ; Center for Integrative Genomics, University of Lausanne Lausanne, Switzerland ; Swiss-Prot group, SIB Swiss Institute of Bioinformatics Lausanne, Switzerland.
authors.forename: Ioannis
authors.initials: I
authors.lastname: Xenarios
keywords: GRN; MIS; T-Helper; algorithms; boolean modeling; cancer pathways; miRNA; qualitative modeling