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When quoting this document, please refer to the following
DOI: 10.4230/DagSemProc.09091.4
URN: urn:nbn:de:0030-drops-19929
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2009/1992/
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Gilbert, David Roger ; Breitling, Rainer ; Heiner, Monika

BioModel Engineering: Its role in Systems Biology and Synthetic Biology

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09091.GilbertDavidRoger.ExtAbstract.1992.pdf (0.06 MB)


Abstract

BioModel Engineering takes place at the interface of computing
science, mathematics, engineering and biology, and provides a
systematic approach for designing, constructing and analyzing
computational models of biological systems. Some of its central
concepts are inspired by efficient software engineering strategies. BioModel Engineering does not aim at engineering biological systems
per se, but rather aims at describing their structure and behavior,
in particular at the level of intracellular molecular processes,
using computational tools and techniques in a principled way.

The two major application areas of BioModel Engineering are systems
biology and synthetic biology. In the former, the aim is the design
and construction of models of existing biological systems, which
explain observed properties and predict the response to experimental
interventions; in the latter, BioModel Engineering is used as part
of a general strategy for designing and constructing synthetic
biological systems with novel functionalities.

The overall steps in building computational models in a BioModel
Engineering framework are: Problem Identification,
Model Construction,
Static and Dynamic Analysis,
Simulation, and
Model management and development.

A major theme in BioModel Engineering is that of constructing a
(qualitative) model means (1) finding the structure, (2) obtaining
an initial state and (3) parameter fitting. In an approach that
we have taken, the structure is
obtained by piecewise construction of models from modular parts,
the initial state which describes concentrations of species or
numbers of molecules is obtained by analysis of the structure, and
parameter fitting comprises determining the rate parameters of the
kinetic equations by reference to trusted data.

Model checking can play a key role in BioModel Engineering -- for
example in recent work we have shown
how parameter estimation can be achieved by characterising the
desired behaviour of a model with a temporal logic property and
altering the model to make it conform to the property as determined
through model checking.

BibTeX - Entry

@InProceedings{gilbert_et_al:DagSemProc.09091.4,
  author =	{Gilbert, David Roger and Breitling, Rainer and Heiner, Monika},
  title =	{{BioModel Engineering: Its role in Systems Biology and Synthetic Biology}},
  booktitle =	{Formal Methods in Molecular Biology},
  pages =	{1--2},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9091},
  editor =	{Rainer Breitling and David Roger Gilbert and Monika Heiner and Corrado Priami},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2009/1992},
  URN =		{urn:nbn:de:0030-drops-19929},
  doi =		{10.4230/DagSemProc.09091.4},
  annote =	{Keywords: Biochemical systems, models, design, construction, systems biology, synthetic biology, model checking.}
}

Keywords: Biochemical systems, models, design, construction, systems biology, synthetic biology, model checking.
Collection: 09091 - Formal Methods in Molecular Biology
Issue Date: 2009
Date of publication: 05.05.2009


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