Abstract
Modelling in systems biology often involves the integration of component models into larger composite models. How to do this systematically and efficiently is a significant challenge: coupling of components can be unidirectional or bidirectional, and of variable strengths. We adapt the waveform relaxation (WR) method for parallel computation of ODEs as a general methodology for computing systems of linked submodels. Four test cases are presented: (i) a cascade of unidirectionally and bidirectionally coupled harmonic oscillators, (ii) deterministic and stochastic simulations of calcium oscillations, (iii) single cell calcium oscillations showing complex behaviour such as periodic and chaotic bursting, and (iv) a multicellular calcium model for a cell plate of hepatocytes. We conclude that WR provides a flexible means to deal with multitime-scale computation and model heterogeneity. Global solutions over time can be captured independently of the solution techniques for the individual components, which may be distributed in different computing environments.
Highlights
A component-based methodology is explicitly or implicitly widely applied to the understanding and modelling of biological systems
The above formulation suggests that a generic form for any submodel should be provided with the form (4) with a dummy flux term. This term is set to zero, but as a component in an integrated model, this term can be formed according to flux contributions from the interactions of linked components. The advantage of this formulation is to provide the flexibility to link to other potential models without altering the internal structure of the original model when the waveform relaxation (WR) method, which will be introduced in Section 3, is applied
Here we present the WR method for a system specified by ordinary differential equations (ODEs), the methodology is applicable to many kinds of system specification
Summary
A component-based methodology is explicitly or implicitly widely applied to the understanding and modelling of biological systems. This is often more consistent with developing understanding of the system through the study of separate, isolated components, and makes it possible to update model components individually as knowledge of the detailed biology evolves This approach provides a framework for integrating heterogeneous models (as components of a larger system), which can be distributed in different computational environments. (iv) It should support linking components represented in different software environments, so as to allow new models to be constructed from existing models with minimal changes These basic requirements call for a general framework based on a combination of modular, object-oriented design and agent-oriented design.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: EURASIP Journal on Bioinformatics and Systems Biology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
