Nutrition Research and the Impact of Computational Systems Biology

Mark T Mc Auley, Carole J Proctor, Bernard M Corfe, Geraldine J Cuskelly, Kathleen M Mooney

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Abstract

The value of computational modelling in improving our understanding of complex nutrient-based pathways is becoming increasingly recognised. This is due to the integral role that computer modelling is playing within the multidisciplinary field of systems biology, where in silico quantitative simulations are being used to compliment more traditional wet-laboratory investigations. A large number of computational models are accessible via the Biomodels database, an archive of openly available peer reviewed models of biological systems. Moreover, there has been an explosion in the availability of free modelling software tools that can be used to assemble and simulate the dynamic behaviour of nutrient mediated systems. Computational modelling will continue to play an increasingly significant role in nutrition research. Thus, it is important that freely accessible models and resources relevant to nutrition research are highlighted. In response to these needs, we firstly examined the Biomodels database, to identify and categorise nutrition themed models. The outcome of the analysis revealed 163 nutrition themed models. These models are mainly cellular in nature, with intracellular representations of calcium oscillations the most common. Secondly, a generic nutrition centred modelling framework was used, to explore recent advances, data repositories and softwarerelevant to model building. We conclude this paper by using our review findings to discuss areas of nutrition that could further exploit the potential of computational modelling in the future.
Original languageEnglish
Pages (from-to)271-285
JournalJ Comput Sci Syst Biol 6: 271-285.
Volume6
Issue number5
Early online date7 Oct 2013
DOIs
Publication statusE-pub ahead of print - 7 Oct 2013

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    Mc Auley, M. T., Proctor, C. J., Corfe, B. M., Cuskelly, G. J., & Mooney, K. M. (2013). Nutrition Research and the Impact of Computational Systems Biology. J Comput Sci Syst Biol 6: 271-285., 6(5), 271-285. https://doi.org/10.4172/jcsb.1000122