Abstract
The first step in model building involves identifying previous models. This is a key step as the model may have been built before and can be modified. If no suitable model exists, it is necessary to assemble a new one. The first stage of building a new model involves clearly defining a hypothesis. This step should be informed by clear thinking and it is not recommended to commence model assembly devoid of a well-defined hypothesis. A well-defined hypothesis will lay the foundation for a worthwhile model and will inform its boundary points. Conversely, a model with a poorly defined hypothesis or no hypothesis at all can rapidly evolve into a cumbersome description of the biology with limited utility. Unfortunately, there are too many examples of models which are excessively descriptive.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Mc Auley, M.T., et al. 2012. A whole-body mathematical model of cholesterol metabolism and its age-associated dysregulation. BMC Systems Biology 6 (1): 130.
Le Novere, N., et al. 2009. The systems biology graphical notation. Nature Biotechnology 27 (8): 735–741.
Le Novere, N., et al. 2011. Systems biology graphical notation: Entity relationship language level 1 (version 1.2). Available from Nature Precedings. http://dx.doi.org/10.1038/npre.2011.5902.1.
Junker, B.H., C. Klukas, and F. Schreiber. 2006. VANTED: A system for advanced data analysis and visualization in the context of biological networks. BMC Bioinformatics 7 (1): 109.
Abell, M.L. and J.P. Braselton. 2016. Differential equations with mathematica. New York: Academic Press.
Schmidt, H., and M. Jirstrand. 2005. Systems biology toolbox for MATLAB: A computational platform for research in systems biology. Bioinformatics 22 (4): 514–515.
Barnes, B. and G.R. Fulford. 2011. Mathematical modelling with case studies: A differential equations approach using Maple and MATLAB, vol. 25. Boca Raton: CRC Press.
Soetaert, K., J. Cash, and F. Mazzia, Solving differential equations in R. Berlin: Springer Science & Business Media.
Lopez, C.F., et al. 2013. Programming biological models in Python using PySB. Mol Syst Biol 9: 646.
Bartocci, E., and P. Lio. 2016. Computational modeling, formal analysis, and tools for systems biology. PLoS Computational Biology 12 (1): e1004591.
Hoops, S., et al. 2006. COPASI—A COmplex PAthway SImulator. Bioinformatics 22 (24): 3067–3074.
Funahashi, A., et al. 2003. Cell designer: A process diagram editor for gene-regulatory and biochemical networks. Biosilico 1 (5): 159–162.
Mendes, P., et al. 2009. Computational modeling of biochemical networks using COPASI. In Systems biology, 17–59. Berlin: Springer.
Morgan, A.E., et al. 2016. Mathematically modelling the dynamics of cholesterol metabolism and ageing. Biosystems 145: 19–32.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Mc Auley, M.T. (2019). Model Building: Part One. In: Computer Modelling for Nutritionists. Springer, Cham. https://doi.org/10.1007/978-3-319-39994-2_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-39994-2_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-39992-8
Online ISBN: 978-3-319-39994-2
eBook Packages: Chemistry and Materials ScienceChemistry and Material Science (R0)