Computational challenges of systems biology

Finkelstein, A.; Hetherington, James; Li, Linzhong; Margoninski, O; Saffrey, Peter; Seymour, Robert M.; Warner, Alan

doi:10.1109/mc.2004.1297236

Cited by 68 publications

(48 citation statements)

References 6 publications

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“…In [13], hybrid automata are used to model the Delta-Notch mechanism, which directs differentiation in various natural systems. In [11], computational challenges of systems biology are described and various approaches for achieving them are discussed. A similar motivation for model-driven engineering approaches is discussed in [36].…”

Section: Discussionmentioning

confidence: 99%

On Using Divide and Conquer in Modeling Natural Systems

Setty

Cohen

Mayo

et al. 2009

Algorithmic Bioprocesses

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In recent years, we have been studying approaches to the realistic modeling of natural systems, especially biological systems. We have tested several of these in a project devoted to modeling pancreatic organogenesis, a complex system that dynamically promotes structural and molecular development. Here, we describe one of these approaches-a kind of 'divide and conquer' technique, in which the system is disassembled into modules to specify behaviors on the scale of the organ (i.e., morphogenesis) and the cell (i.e., molecular interactions). At run-time, these modules are re-assembled to direct development in individual cells. This approach employs multi-scaling and dynamics, two important characteristics of natural systems, but avoids cross-scaling. It thus appears to be useful for systems in which the importance of cross-scaling seems to be less significant, such as the development of phyllotaxis in plants. In pancreatic organogenesis, cross-scaling was found to be a significant characteristic, and thus by using 'divide and conquer' we could cover only its preliminary stages. We discuss the approach and our use of it, as well as he various methods to analyze the achievements and limitations of the end result.

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Section: Discussionmentioning

confidence: 99%

On Using Divide and Conquer in Modeling Natural Systems

Setty

Cohen

Mayo

et al. 2009

Algorithmic Bioprocesses

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“…This comprehensive "metamodel" (Finkelstein et al, 2004), underpins the development of the tools presented in this paper so it is reviewed here.…”

Section: Metamodellingmentioning

confidence: 99%

“…All of this information is useful in understanding existing work and taking it forward. The need for information management is discussed in greater depth in Finkelstein et al (2004). A set of minimum standards for the metadata required to properly annotate a biological model has been defined (Novére, Finney, Hucka, & Bhalla, 2005).…”

Section: The Need For Information Managementmentioning

confidence: 99%

Addressing the challenges of multiscale model management in systems biology

Hetherington¹,

Bogle²,

Saffrey³

et al. 2007

Computers & Chemical Engineering

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stract athematical and computational modelling are emerging as important techniques for studying the behaviour of complex biological systems. argue that two advances are necessary to properly leverage these techniques: firstly, the ability to integrate models developed and executed on arate tools, without the need for substantial translation and secondly, a comprehensive system for storing and man-ageing not only the models mselves but also the parameters and tools used to execute those models and the results they produce. A framework for modelling with these tures is described here. We have developed of a suite of XML-based services used for the storing and analysis of models, model parameters results, and tools for model integration. We present these here, and evaluate their effectiveness using a worked example based on part of the atocyte glycogenolysis system.

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“…The complete cascade from the genome, proteome, metabolome, physiome to health constitutes multi-scale, multi-science systems, and crosses many orders of magnitude in temporal and spatial scales [2,3]. Studying biological modules, their design principles, and their mutual interactions, through an interplay between experiments and modeling and simulations, should lead to an understanding of biological function and to a prediction of the effects of perturbations (e.g.…”

Section: Introductionmentioning

confidence: 99%