In silico modeling of biochemical pathways


Published: 28 September 2021
Abstract views:
1224


PDF:
275
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Authors

  • Paolo Milazzo Department of Computer Science, University of Pisa, Pisa; Inter-universitary Center for the Promotion of the 3Rs Principles in Teaching and Research (Centro 3R), Pisa, Italy.
  • Roberta Gori Department of Computer Science, University of Pisa, Pisa, Italy.
  • Alessio Micheli Department of Computer Science, University of Pisa, Pisa; Inter-universitary Center for the Promotion of the 3Rs Principles in Teaching and Research (Centro 3R), Pisa, Italy.
  • Lucia Nasti Department of Computer Science, University of Pisa, Pisa, Italy.
  • Marco Podda Department of Computer Science, University of Pisa, Pisa, Italy.

We present in silico modeling methods for the investigation of dynamical properties of biochemical pathways, that are chemical reaction networks underlying cell functioning. Since pathways are (complex) dynamical systems, in-silico models are often studied by applying numerical integration techniques for Ordinary Differential Equations (ODEs), or stochastic simulation algorithms. However, these techniques require a rather accurate knowledge of the kinetic parameters of the modeled chemical reactions. Moreover, in the case of very complex reaction networks, in silico analysis can become unfeasible from the computational viewpoint. Consequently, in the last few years several approaches have been proposed that focus on estimating or predicting dynamical properties from the analysis of the structure of the biochemical pathway. This means that the analysis focuses more on the interaction patterns than on the kinetic parameters, and this usually makes it possible to deduce the role of each molecule and how each molecule qualitatively influences each other, by abstracting away from quantitative details about concentrations and reaction rates.


Milazzo, P., Gori, R., Micheli, A., Nasti, L., & Podda, M. (2021). <em>In silico</em> modeling of biochemical pathways. Biomedical Science and Engineering, 3(1). https://doi.org/10.4081/bse.142

Downloads

Download data is not yet available.

Citations

Similar Articles

You may also start an advanced similarity search for this article.