BioModel Engineering with Petri Nets

Blätke, Mary Ann; Heiner, Monika; Marwan, Wolfgang

doi:10.1016/b978-0-12-801213-0.00007-1

Cited by 28 publications

(31 citation statements)

References 63 publications

(73 reference statements)

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“…Our model is validated by domain experts, as well as by formal verification of desired invariants that should hold for biological pathways [4,5,6]. We further validate that simulating loss of function (LoF) mutations of interest complies with known experimental findings.…”

Section: Introductionmentioning

confidence: 71%

“…CCS uses stochastic Petri net (SPN) simulation for examining the actual and potential phenotypic effects of perturbation of a network known to be involved in comorbidities to predict new roles for genes in the comorbid conditions. SPN is a mathematical formalism [4,5] where stochastic time-delays are assigned to each system event (e.g., enzymatic reaction) during simulation, enabling generation of dynamic behavior. We applied our approach to explore the molecular convergence of autism spectrum disorder and inflammatory bowel disorder.…”

Section: Introductionmentioning

confidence: 99%

“…A Petri net [4–6] is a discrete event simulation approach developed for system representation that enables concurrency and synchronization properties. This established formal and graphical technique abstracts systems dynamics with a graph composed of arcs and nodes, with tokens moving between the nodes.…”

Section: Introductionmentioning

confidence: 99%

“…A stochastic Petri net (SPN) [4–6] incorporates the notion of time into a Petri net and allows for the representation of rates of biological reactions and processes. A transition is assigned with an exponentially-distributed random variable with a parameter that defines the firing rate, i.e., the delay between the enabling and the firing of the transition.…”

Section: Introductionmentioning

confidence: 99%

“…Petri nets are appropriate for modeling biological systems qualitatively, when the kinetic coefficients and the flux rates are unknown [4,5]. The non-deterministic feature of stochastic Petri nets is used to cope with this incomplete data and to simulate the biological system at hand [43].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A model-driven methodology for exploring complex disease comorbidities applied to autism spectrum disorder and inflammatory bowel disease

Somekh

Peleg

Eran

et al. 2016

Journal of Biomedical Informatics

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We propose a model-driven methodology aimed to shed light on complex disorders. Our approach enables exploring shared etiologies of comorbid diseases at the molecular pathway level. The method, Comparative Comorbidities Simulation (CCS), uses stochastic Petri net simulation for examining the phenotypic effects of perturbation of a network known to be involved in comorbidities to predict new roles for mutations in comorbid conditions. To demonstrate the utility of our novel methodology, we investigated the molecular convergence of autism spectrum disorder (ASD) and inflammatory bowel disease (IBD) on the autophagy pathway. In addition to validation by domain experts, we used formal analyses to demonstrate the model’s self-consistency. We then used CCS to compare the effects of loss of function (LoF) mutations previously implicated in either ASD or IBD on the autophagy pathway. CCS identified similar dynamic consequences of these mutations in the autophagy pathway. Our method suggests that two LoF mutations previously implicated in IBD may contribute to ASD, and one ASD-implicated LoF mutation may play a role in IBD. Future targeted genomic or functional studies could be designed to directly test these predictions.

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Section: Introductionmentioning

confidence: 71%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A model-driven methodology for exploring complex disease comorbidities applied to autism spectrum disorder and inflammatory bowel disease

Somekh

Peleg

Eran

et al. 2016

Journal of Biomedical Informatics

Self Cite

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The best models of metabolism

Voit

2017

WIREs Mechanisms of Disease

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Biochemical systems are among of the oldest application areas of mathematical modeling. Spanning a time period of over one hundred years, the repertoire of options for structuring a model and for formulating reactions has been constantly growing, and yet, it is still unclear whether or to what degree some models are better than others and how the modeler is to choose among them. In fact, the variety of options has become overwhelming and difficult to maneuver for novices and experts alike. This review outlines the metabolic model design process and discusses the numerous choices for modeling frameworks and mathematical representations. It tries to be inclusive, even though it cannot be complete, and introduces the various modeling options in a manner that is as unbiased as that is feasible. However, the review does end with personal recommendations for the choices of default models.

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