Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
2070391 | Progress in Biophysics and Molecular Biology | 2008 | 12 Pages |
Abstract
Diseases are complex systems. Modelling them, i.e. systems physiopathology, is a quite demanding, complicated, multidimensional, multiscale process. As such, in order to achieve the goal of the model and further to optimise a rather-time and resource-consuming process, a relevant and easy to practice methodology is required. It includes guidance for validation. Also, the model development should be managed as a complicated process, along a strategy which has been elaborated in the beginning. It should be flexible enough to meet every case. A model is a representation of the available knowledge. All available knowledge does not have the same level of evidence and, further, there is a large variability of the values of all parameters (e.g. affinity constant or ionic current) across the literature. In addition, in a complex biological system there are always values lacking for a few or sometimes many parameters. All these three aspects are sources of uncertainty on the range of validity of the models and raise unsolved problems for designing a relevant model. Tools and techniques for integrating the parameter range of experimental values, level of evidence and missing data are needed.
Keywords
Related Topics
Life Sciences
Biochemistry, Genetics and Molecular Biology
Biophysics
Authors
Jean-Pierre Boissel, Benjamin Ribba, Emmanuel Grenier, Guillemette Chapuisat, Marie-Aimée Dronne,