Literature DB >> 27353233

Modular modelling with Physiome standards.

Michael T Cooling1, David P Nickerson1, Poul M F Nielsen1,2, Peter J Hunter1.   

Abstract

KEY POINTS: The complexity of computational models is increasing, supported by research in modelling tools and frameworks. But relatively little thought has gone into design principles for complex models. We propose a set of design principles for complex model construction with the Physiome standard modelling protocol CellML. By following the principles, models are generated that are extensible and are themselves suitable for reuse in larger models of increasing complexity. We illustrate these principles with examples including an architectural prototype linking, for the first time, electrophysiology, thermodynamically compliant metabolism, signal transduction, gene regulation and synthetic biology. The design principles complement other Physiome research projects, facilitating the application of virtual experiment protocols and model analysis techniques to assist the modelling community in creating libraries of composable, characterised and simulatable quantitative descriptions of physiology. ABSTRACT: The ability to produce and customise complex computational models has great potential to have a positive impact on human health. As the field develops towards whole-cell models and linking such models in multi-scale frameworks to encompass tissue, organ, or organism levels, reuse of previous modelling efforts will become increasingly necessary. Any modelling group wishing to reuse existing computational models as modules for their own work faces many challenges in the context of construction, storage, retrieval, documentation and analysis of such modules. Physiome standards, frameworks and tools seek to address several of these challenges, especially for models expressed in the modular protocol CellML. Aside from providing a general ability to produce modules, there has been relatively little research work on architectural principles of CellML models that will enable reuse at larger scales. To complement and support the existing tools and frameworks, we develop a set of principles to address this consideration. The principles are illustrated with examples that couple electrophysiology, signalling, metabolism, gene regulation and synthetic biology, together forming an architectural prototype for whole-cell modelling (including human intervention) in CellML. Such models illustrate how testable units of quantitative biophysical simulation can be constructed. Finally, future relationships between modular models so constructed and Physiome frameworks and tools are discussed, with particular reference to how such frameworks and tools can in turn be extended to complement and gain more benefit from the results of applying the principles.
© 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.

Entities:  

Keywords:  modelling; modularity; physiome; standards

Mesh:

Year:  2016        PMID: 27353233      PMCID: PMC5134412          DOI: 10.1113/JP272633

Source DB:  PubMed          Journal:  J Physiol        ISSN: 0022-3751            Impact factor:   5.182


  25 in total

1.  Standard virtual biological parts: a repository of modular modeling components for synthetic biology.

Authors:  M T Cooling; V Rouilly; G Misirli; J Lawson; T Yu; J Hallinan; A Wipat
Journal:  Bioinformatics       Date:  2010-02-16       Impact factor: 6.937

2.  Towards building the silicon cell: a modular approach.

Authors:  Jacky L Snoep; Frank Bruggeman; Brett G Olivier; Hans V Westerhoff
Journal:  Biosystems       Date:  2005-10-19       Impact factor: 1.973

3.  A new multiphysics model for the physiological responses of vascular endothelial cells to fluid shear stress.

Authors:  Hyun Goo Kang; Eun Bo Shim; Keun-Shik Chang
Journal:  J Physiol Sci       Date:  2007-10-30       Impact factor: 2.781

Review 4.  Practical application of CellML 1.1: The integration of new mechanisms into a human ventricular myocyte model.

Authors:  David Nickerson; Martin Buist
Journal:  Prog Biophys Mol Biol       Date:  2008-06-23       Impact factor: 3.667

5.  ApiNATOMY: a novel toolkit for visualizing multiscale anatomy schematics with phenotype-related information.

Authors:  Bernard de Bono; Pierre Grenon; Stephen John Sammut
Journal:  Hum Mutat       Date:  2012-05       Impact factor: 4.878

6.  A whole-cell computational model predicts phenotype from genotype.

Authors:  Jonathan R Karr; Jayodita C Sanghvi; Derek N Macklin; Miriam V Gutschow; Jared M Jacobs; Benjamin Bolival; Nacyra Assad-Garcia; John I Glass; Markus W Covert
Journal:  Cell       Date:  2012-07-20       Impact factor: 41.582

7.  The Physiome Model Repository 2.

Authors:  Tommy Yu; Catherine M Lloyd; David P Nickerson; Michael T Cooling; Andrew K Miller; Alan Garny; Jonna R Terkildsen; James Lawson; Randall D Britten; Peter J Hunter; Poul M F Nielsen
Journal:  Bioinformatics       Date:  2011-01-06       Impact factor: 6.937

8.  The Open Physiology workflow: modeling processes over physiology circuitboards of interoperable tissue units.

Authors:  Bernard de Bono; Soroush Safaei; Pierre Grenon; David P Nickerson; Samuel Alexander; Michiel Helvensteijn; Joost N Kok; Natallia Kokash; Alan Wu; Tommy Yu; Peter Hunter; Richard A Baldock
Journal:  Front Physiol       Date:  2015-02-24       Impact factor: 4.566

9.  A reappraisal of how to build modular, reusable models of biological systems.

Authors:  Maxwell L Neal; Michael T Cooling; Lucian P Smith; Christopher T Thompson; Herbert M Sauro; Brian E Carlson; Daniel L Cook; John H Gennari
Journal:  PLoS Comput Biol       Date:  2014-10-02       Impact factor: 4.475

10.  The Cardiac Electrophysiology Web Lab.

Authors:  Jonathan Cooper; Martin Scharm; Gary R Mirams
Journal:  Biophys J       Date:  2016-01-19       Impact factor: 4.033

View more
  5 in total

1.  The Cardiac Physiome Project.

Authors:  Peter J Hunter; Nicolas P Smith
Journal:  J Physiol       Date:  2016-12-01       Impact factor: 5.182

2.  A semantics, energy-based approach to automate biomodel composition.

Authors:  Niloofar Shahidi; Michael Pan; Kenneth Tran; Edmund J Crampin; David P Nickerson
Journal:  PLoS One       Date:  2022-06-03       Impact factor: 3.752

Review 3.  Systems modelling ageing: from single senescent cells to simple multi-cellular models.

Authors:  Alvaro Martinez Guimera; Ciaran Welsh; Piero Dalle Pezze; Nicola Fullard; Glyn Nelson; Mathilde F Roger; Stefan A Przyborski; Daryl P Shanley
Journal:  Essays Biochem       Date:  2017-07-11       Impact factor: 8.000

4.  Modular assembly of dynamic models in systems biology.

Authors:  Michael Pan; Peter J Gawthrop; Joseph Cursons; Edmund J Crampin
Journal:  PLoS Comput Biol       Date:  2021-10-13       Impact factor: 4.475

5.  A novel modular modeling approach for understanding different electromechanics between left and right heart in rat.

Authors:  Nari Kim; Julius D Pronto; David P Nickerson; Andrew J Taberner; Peter J Hunter
Journal:  Front Physiol       Date:  2022-09-13       Impact factor: 4.755

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.