Standard virtual biological parts: A repository of modular modeling components for synthetic biology

Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand.
Bioinformatics (Impact Factor: 4.62). 02/2010; 26(7):925-31. DOI: 10.1093/bioinformatics/btq063
Source: PubMed

ABSTRACT Motivation: Fabrication of synthetic biological systems is greatly enhanced by incorporating engineering design principles and techniques such as computer-aided design. To this end, the ongoing standardization of biological parts presents an opportunity to develop libraries of standard virtual parts in the form of mathematical models that can be combined to inform system design. Results: We present an online Repository, populated with a collection of standardized models that can readily be recombined to model different biological systems using the inherent modularity support of the CellML 1.1 model exchange format. The applicability of this approach is demonstrated by modeling gold-medal winning iGEM machines. Availability and Implementation: The Repository is available online as part of We hope to stimulate the worldwide community to reuse and extend the models therein, and contribute to the Repository of Standard Virtual Parts thus founded. Systems Model architecture information for the Systems Model described here, along with an additional example and a tutorial, is also available as Supplementary information. The example Systems Model from this manuscript can be found at The Template models used in the example can be found at Contact: [email protected]
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    • "The modular nature of SVPs allows new templates to be defined at any desired level of abstraction. In this work, the set of SVP types was extended beyond those described previously [Cooling et al. 2010] to include operators and shims (spacer sequences). A set of promoters acting as two-input logic gates was also defined. "
    ACM Journal on Emerging Technologies in Computing Systems 12/2014; 11(3):1-19. DOI:10.1145/2631921 · 0.83 Impact Factor
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    • "Here, we focus on the use of CellML to provide general purpose " plug and play " of mathematical models and model configuration in OpenCMISS applications. CellML (Cuellar et al., 2003) 3 is an XML format for encoding mathematical models in a modular and reusable manner (Nickerson and Buist, 2008; Cooling et al., 2010). See Section 2 below for a general introduction to the mathematical framework provided by CellML. "
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    ABSTRACT: OpenCMISS is an open-source modeling environment aimed, in particular, at the solution of bioengineering problems. OpenCMISS consists of two main parts: a computational library (OpenCMISS-Iron) and a field manipulation and visualisation library (OpenCMISS-Zinc). OpenCMISS is designed for the solution of coupled multi-scale, multi-physics problems in a general-purpose parallel environment. CellML is an XML format designed to encode biophysically based systems of ordinary differential equations and both linear and non-linear algebraic equations. A primary design goal of CellML is to allow mathematical models to be encoded in a modular and reusable format to aide reproducibility and interoperability of modeling studies. In OpenCMISS we make use of CellML models to enable users to configure various aspects of their multi-scale physiological models. This avoids the need for users to be familiar with the OpenCMISS internal code in order to perform customised computational experiments. Examples of this are: cellular electrophysiology models embedded in tissue electrical propagation models; material constitutive relationships for mechanical growth and deformation simulations; time-varying boundary conditions for various problem domains; fluid constitutive relationships and lumped parameter models. In this paper we provide implementation details describing how CellML models are integrated into multi-scale physiological models in OpenCMISS. The external interface OpenCMISS presents to users will also be described, including specific examples exemplifying the extensibility and usability these tools provide the physiological modelling and simulation community. We conclude with some thoughts on future extension of OpenCMISS to make use other community developed information standards, such as FieldML, SED-ML, and BioSignalML. Plans for the integration of accelerator code (GPU and FPGA) generated from CellML models is also discussed.
    Frontiers in Bioengineering and Biotechnology 01/2014; 2:79. DOI:10.3389/fbioe.2014.00079
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    • "The modular approach is widely used in modern engineering, and in the past decade, its importance in modeling biological systems has become evident as well. One reason is that this approach well matches the structure of biological systems on multiple levels: from cells [Hartwell et al, 1999] to organs and whole organisms [Cooling et al, 2010]. Snoep et al. [Snoep et al, 2006] describe their vision of the construction of a comprehensive model describing a complete cellular system at the reaction level (i.e. "
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    ABSTRACT: Motivation: Modeling of complex biological systems such as cells, organs or even whole organisms is not a trivial task because of their intricate structure. Although modern computers allow simulation for quite complex models, such models are difficult to support and work with. Modular approach facilitates the creation of complex models by representing them as combinations of submodels. On the other hand, there are a large number of models describing particular subsystems created by different authors using different formalisms and scales. These models may be reused as "bricks" in the creation of comprehensive overall models. Results: We have developed a modular approach to the modeling of complex biological systems. It includes a formal definition of graphical notation for modular models, an algorithm for the transformation of a modular model into a non-modular model which is appropriate for simulation using standard methods for solving ordinary differential equations (ODE), and an algorithm for simulating modular model based on the agent-model principles. The approach was implemented in software plug-in for BioUML platform. Availability: The developed software and the source code are freely available as a part of BioUML in both standalone and web versions at
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