Fusing and Composing Macromolecular Regulatory Network Models Ranjit Randhawa* Clifford A. Shaffer*...

Fusing and Composing Macromolecular Regulatory Network Models

Ranjit Randhawa*Clifford A. Shaffer*

John J. Tyson+

Departments of Computer Science* and Biology+

Virginia TechBlacksburg, VA 24061

Regulatory Network Modeling Wish to deduce physiological properties of a

cell from wiring diagrams of control systems

Frogegg Model

Budding Yeast Model

Wiring diagrams are converted to reactions for simulation

Example: Chen and Tyson’s 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.

Budding Yeast Wiring Diagram

Budding Yeast Model

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).

Solution

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

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.

Sample Models

Fused and Composed Models

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

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

Fusion Tool Setup Wizard

Species Mapping Table

Reaction Mapping Table

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

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

Composition Hierarchy

<model id="Big"> <listOfCompartments> <compartment id="comp1" volume="1"/> </listOfCompartments> <listOfSubmodels> <model id="Little"> <listOfCompartments> <compartment id="comp2" volume="1"/> </listOfCompartments> </model> </listOfSubmodels></model>

Links

<link>

<from object="comp1"/>

<to object="Submodel_Little"

<subobject object="comp2"/>

</to>

</link>

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.

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.

Toggle Switch

Iconified Toggle Switch

Toggle Switch Component

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.

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]