Fusing and Composing Macromolecular Regulatory Network Models

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Fusing and Composing Macromolecular Regulatory
Network Models

• Ranjit Randhawa
• Clifford A. Shaffer
• John J. Tyson
• Departments of Computer Science and Biology
• Virginia Tech
• Blacksburg, VA 24061

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Regulatory Network Modeling

• Wish to deduce physiological properties of a cell
  from wiring diagrams of control systems

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Frogegg Model
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Budding Yeast Model

• Wiring diagrams are converted to reactions for
  simulation
• Example Chen and Tysons budding yeast model
  contains over 30 ODEs, some nonlinear.
• About 140 rate constant parameters
• Validate model by comparing simulation results
  against morphological outcomes from over 100
  mutants defective in the regulatory network.

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Budding Yeast Wiring Diagram
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Budding Yeast Model
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Problem

• These models are reaching the limits of human
  comprehension
• Making the model suitable for stochastic
  simulation increases the number of reactions by a
  factor of 3-5.
• Models of the Mammalian cell cycle will require
  100-1000 (more for stochastic simulation).

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Solution

• Some mechanism must be found to describe models
  as collections of small building blocks that are
  combined to form the full model.

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Systems Biology Markup Language

• SBML is the current standard interchange language
  within the community of systems biology modelers.
• We implement our proposals within the context of
  SBML language additions.

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Sample Models
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Fused and Composed Models
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Fusion

• Given two or more existing models, we wish to
  create a new model that combines the information.
• Remains standard SBML
• We provide a tool to support users combining
  models.
• Implemented in wizard style

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Fusion Matching Tables

• Fusion is done primarily by defining matching of
  SBML components
• Compartments, reactions, species, etc.
• A series of matching tables
• Order is important to deal with dependencies

mf m1 m2
1 A A A
2 B B
3 D D
mf m1 m2
1 A1 A
2 C B D
3 A2 A
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Fusion Tool Setup Wizard
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Species Mapping Table
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Reaction Mapping Table
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Composition

• Connects submodels together to form a hierarchy
  of models
• Submodels are each valid SBML models
• Add language features to SBML to support
  composition
• Describe hierarchy
• Describe interactions, links, replacements
• No information hiding within models

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Composition and the Fusion Wizard

• There are significant similarities between fusion
  and composition
• Fusion defines a series of steps taken to merge
  models
• Series of steps captured by the fusion tool can
  be viewed as an audit trail used in generating
  the mapping tables
• Precisely this same information can be used to
  describe the set of instructions needed to
  connect/link the submodels for composition

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Composition Hierarchy

• ltmodel id"Big"gt
• ltlistOfCompartmentsgt
• ltcompartment id"comp1" volume"1"/gt
• lt/listOfCompartmentsgt
• ltlistOfSubmodelsgt
• ltmodel id"Little"gt
• ltlistOfCompartmentsgt
• ltcompartment id"comp2"
• volume"1"/gt
• lt/listOfCompartmentsgt
• lt/modelgt
• lt/listOfSubmodelsgt
• lt/modelgt

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Links

• ltlinkgt
• ltfrom object"comp1"/gt
• ltto object"Submodel_Little"
• ltsubobject object"comp2"/gt
• lt/togt
• lt/linkgt

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Is Composition the Right Model?

• Composition allows us to take existing models and
  use them as components to build larger models
• No information hiding
• Submodels might fit together more or less well
• Links let us replace things in one model with
  things in another
• Good for legacy models(?)
• We might do better to build models from
  components designed to work as components, with
  proper information hiding.

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Aggregation

• In aggregation, models are built up from
  components
• Each component could be, for example, a
  collection of reactions
• This collection exposes certain variables for
  input/output via ports
• Hopefully this is a natural concept for modelers
• Not intended as a solution for reusing legacy
  models.

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Toggle Switch
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Iconified Toggle Switch
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Toggle Switch Component
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Flattening

• Flattening generates a standard SBML file from
  our modified file, for the purpose of running
  simulations, etc.
• An automated form of fusion.
• The additional language features provide what the
  user would provide during fusion, so automation
  is possible.

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Summary

• We recognize four distinct activities related to
  model decomposition Status
• Fusion Take existing models and merge them
  Implemented
• Composition Build up from existing models, no
  information hiding Implemented
• Aggregation Build up from building blocks,
  controlled interfaces Designing stage
• Flattening Merge the building blocks back into a
  flat (non-composed) model (for making
  simulation runs) Implemented