ALC: automated reduction of rule-based models

Koschorreck, Markus; Gilles, Ernst Dieter

doi:10.1186/1752-0509-2-91

Cited by 11 publications

(11 citation statements)

References 37 publications

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“…the binding at a phosphorylation site can only occur after the site has been phosphorylated). This type of interaction has been introduced in [6,19] and is employed for model reduction purposes.…”

Section: Resultsmentioning

confidence: 99%

“…In the context of combinatorial reaction networks, processes and interactions are already introduced in [6,7,19] and a graph with nodes representing processes and edges representing interactions is used in [7]. While in [6,7,19] the focus is on reduction of models of combinatorial reaction networks, the PIM concept focuses on the set-up of two consistent models in different formalisms.…”

Section: Resultsmentioning

confidence: 99%

“…While in [6,7,19] the focus is on reduction of models of combinatorial reaction networks, the PIM concept focuses on the set-up of two consistent models in different formalisms.…”

Section: Resultsmentioning

confidence: 99%

“…Many tools facilitate rule-based modeling, for example, BioNetGen [17], ALC [19] and Kappa [20]. These tools require a text-based specification of rule-based models.…”

Section: Introductionmentioning

confidence: 99%

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The Process-Interaction-Model: a common representation of rule-based and logical models allows studying signal transduction on different levels of detail

et al. 2012

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BackgroundSignaling systems typically involve large, structured molecules each consisting of a large number of subunits called molecule domains. In modeling such systems these domains can be considered as the main players. In order to handle the resulting combinatorial complexity, rule-based modeling has been established as the tool of choice. In contrast to the detailed quantitative rule-based modeling, qualitative modeling approaches like logical modeling rely solely on the network structure and are particularly useful for analyzing structural and functional properties of signaling systems.ResultsWe introduce the Process-Interaction-Model (PIM) concept. It defines a common representation (or basis) of rule-based models and site-specific logical models, and, furthermore, includes methods to derive models of both types from a given PIM. A PIM is based on directed graphs with nodes representing processes like post-translational modifications or binding processes and edges representing the interactions among processes. The applicability of the concept has been demonstrated by applying it to a model describing EGF insulin crosstalk. A prototypic implementation of the PIM concept has been integrated in the modeling software ProMoT.ConclusionsThe PIM concept provides a common basis for two modeling formalisms tailored to the study of signaling systems: a quantitative (rule-based) and a qualitative (logical) modeling formalism. Every PIM is a compact specification of a rule-based model and facilitates the systematic set-up of a rule-based model, while at the same time facilitating the automatic generation of a site-specific logical model. Consequently, modifications can be made on the underlying basis and then be propagated into the different model specifications – ensuring consistency of all models, regardless of the modeling formalism. This facilitates the analysis of a system on different levels of detail as it guarantees the application of established simulation and analysis methods to consistent descriptions (rule-based and logical) of a particular signaling system.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

“…While in [6,7,19] the focus is on reduction of models of combinatorial reaction networks, the PIM concept focuses on the set-up of two consistent models in different formalisms.…”

Section: Resultsmentioning

confidence: 99%

“…Many tools facilitate rule-based modeling, for example, BioNetGen [17], ALC [19] and Kappa [20]. These tools require a text-based specification of rule-based models.…”

Section: Introductionmentioning

confidence: 99%

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The Process-Interaction-Model: a common representation of rule-based and logical models allows studying signal transduction on different levels of detail

et al. 2012

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“…Step 1: One generates a complete mechanistic ODE model of the considered combinatorial reaction network using e.g. B IO N ET G EN or ALC [ 19 , 29 ]. Furthermore, one has to define input and output variables.…”

Section: Resultsmentioning

confidence: 99%

Exact model reduction of combinatorial reaction networks

2008

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Background: Receptors and scaffold proteins usually possess a high number of distinct binding domains inducing the formation of large multiprotein signaling complexes. Due to combinatorial reasons the number of distinguishable species grows exponentially with the number of binding domains and can easily reach several millions. Even by including only a limited number of components and binding domains the resulting models are very large and hardly manageable. A novel model reduction technique allows the significant reduction and modularization of these models.

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Two Challenges of Systems Biology

Hlavacek

2011

Handbook of Statistical Systems Biology

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ALC: automated reduction of rule-based models

Cited by 11 publications

References 37 publications

The Process-Interaction-Model: a common representation of rule-based and logical models allows studying signal transduction on different levels of detail

The Process-Interaction-Model: a common representation of rule-based and logical models allows studying signal transduction on different levels of detail

Exact model reduction of combinatorial reaction networks

Two Challenges of Systems Biology

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