1 / 8

Introduction to Rule-based modeling

Introduction to Rule-based modeling. … using BioNetGen. When/why should we use RBM. Many interacting components Multiple components interact with each other and create large ensembles of complexes . Multiple states for each component

carney
Télécharger la présentation

Introduction to Rule-based modeling

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Introduction to Rule-based modeling … using BioNetGen

  2. When/why should we use RBM • Many interacting components Multiple components interact with each other and create large ensembles of complexes. • Multiple states for each component Post-translational modifications alter the behavior of the proteins in the system. • RB makes modeling actually “possible” Use only a set of biologically sensible rules in order to generate the full system.

  3. In biochemical modeling, what do we • usually know? Information about protein-interactions Information about kinetic laws • need to have? Consistent system of interactions of the required components Set of ODE’s to describe the behavior of this system Flexibility to define observables from our system • want to avoid? Missing any important interactions Making unjustified assumptions

  4. For example… RULE-BASED FORMULATION FOR LARGE ODE SYSTEMS (A) Localization &Contact Map (B) State transition Reaction Network Define the differential equation for each specie manually Define mechanistic rules, and generate the system of equations automatically

  5. Rule-based modeling concepts

  6. Structure of a RB model • Parameters: Define the parameters that govern the dynamics of the system (rate constants, the values for initial concentrations of species in the biological system) • Molecule types: Define molecules, including components and allowed component states • Seed species: Define the initial state of system (initial species and their concentrations) • Observables: Define model outputs, which are functions of concentrations of species having particular attributes • Reaction rules: Define rules that describe how molecules interact • Actions: Methods to generate and simulate network

  7. Summary of possible rules Five basic transformations • Add a bond “A(a)+B(b) –> A(a!1).B(b!1) k_bind” • Delete a bond “A(a!1).B(b!1) –> A(a) + B(b)k_unbind” • Change a component state label “EGFR(Y1068 ~ P) –>EGFR(Y1068 ~ U) k_dephos” • Add a molecule “I() –>I() + A(a,Y~U) k_synth” • Delete a molecule “A() –>Trash() k_deg”

  8. Example

More Related