FoPA: identifying perturbed signaling pathways in clinical conditions using formal methods

BMC Bioinformatics
Fatemeh MansooriKaveh Kavousi

Abstract

Accurate identification of perturbed signaling pathways based on differentially expressed genes between sample groups is one of the key factors in the understanding of diseases and druggable targets. Most pathway analysis methods prioritize impacted signaling pathways by incorporating pathway topology using simple graph-based models. Despite their relative success, these models are limited in describing all types of dependencies and interactions that exist in biological pathways. In this work, we propose a new approach based on the formal modeling of signaling pathways. Signaling pathways are formally modeled, and then model checking tools are applied to find the likelihood of perturbation for each pathway in a given condition. By adopting formal methods, various complex interactions among biological parts are modeled, which can contribute to reducing the false-positive rate of the proposed approach. We have developed a tool named Formal model checking based pathway analysis (FoPA) based on this approach. FoPA is compared with three well-known pathway analysis methods: PADOG, CePa, and SPIA on the benchmark of 36 GEO datasets from various diseases by applying the target pathway technique. This validation technique eliminates th...Continue Reading

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Datasets Mentioned

BETA
GSE4183
GSE18842
GSE8671
GSE16759

Methods Mentioned

BETA
exome sequencing

Software Mentioned

Plage
R
SPIA
GSA
Pathway
- Express
R limma package
Globaltest
KEGGdzPathwaysGEO
FoPA

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