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The complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems.
The flexible, intuitive and extensible nature of agent-based modelling makes it well-suited to modelling biological systems.
Integrating agent-based models with their continuum counterparts, as has been tried elsewhere [ 31, 68 71], is an elegant and, from a biological perspective, a more precise way of addressing the non-trivial problem of modelling biological systems.
Motivation: One of the challenging questions in modelling biological systems is to characterize the functional forms of the processes that control and orchestrate molecular and cellular phenotypes.
Availability: Source code and binaries for Linux, Mac and Windows are available at http://www.infobiotics.org/infobiotics-workbench/; released under the GNU General Public License (GPL) version 3. Contact: [email protected] A comprehensive and generic framework for modelling biological systems from the molecular to organismal scales remains a distant prospect.
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Based on our positive experience, we propose that the friendly, yet formal, OPM modeling framework is a tool for modeling biological systems, whose adoption would benefit the emerging domain of systems biology.
Moreover, the lack of the process as a stand-alone concept in the OO modeling approach is a major hindrance for modeling biological systems, which are mostly process-intensive.
RODNEY BROOKS, the 45-year-old director of the Artificial Intelligence Laboratory at the Massachusetts Institute of Technology, has spent most of his career engrossed in the question of how to model biological systems.
The deluge of genomic information would, the theory went, be funnelled into powerful computers, which would then be able to model biological systems, figure out how they went wrong, and design drugs to fix them.
Then the parameter estimation is essential for modeling biological systems.
The authors concluded that the FO models are more suitable to model biological systems with memory, than their integer-order counterparts.
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