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Designing and encoding models for synthetic biology
Author(s) -
Lukas Endler,
Nicolás Rodríguez,
Nick Juty,
Vijayalakshmi Chelliah,
Camille Laibe,
Chen Li,
Nicolas Le Novère
Publication year - 2009
Publication title -
journal of the royal society interface
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.655
H-Index - 139
eISSN - 1742-5689
pISSN - 1742-5662
DOI - 10.1098/rsif.2009.0035.focus
Subject(s) - markup language , sbml , computer science , systems biology , synthetic biology , encode , reuse , software , component (thermodynamics) , key (lock) , domain (mathematical analysis) , computational biology , theoretical computer science , biology , programming language , xml , gene , mathematics , operating system , ecology , biochemistry , computer security , thermodynamics , physics , mathematical analysis
A key component of any synthetic biology effort is the use of quantitative models. These models and their corresponding simulations allow optimization of a system design, as well as guiding their subsequent analysis. Once a domain mostly reserved for experts, dynamical modelling of gene regulatory and reaction networks has been an area of growth over the last decade. There has been a concomitant increase in the number of software tools and standards, thereby facilitating model exchange and reuse. We give here an overview of the model creation and analysis processes as well as some software tools in common use. Using markup language to encode the model and associated annotation, we describe the mining of components, their integration in relational models, formularization and parametrization. Evaluation of simulation results and validation of the model close the systems biology 'loop'.

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