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Hybrid modelling of biological systems: current progress and future prospects
Fei Liu1, Monika Heiner2, David Gilbert3
1School of Software Engineering, South China University of Technology, Guangzhou 510006, P.R. China.
Briefings in Bioinformatics
|March 30, 2022
Summary
Integrated biological modelling requires hybrid methods for a holistic view. This review explores popular hybrid approaches in systems biology, highlighting their origins, simulation, and future research needs for enhanced biological system understanding.
Area of Science:
- Systems Biology
- Computational Biology
- Biochemical Modelling
Background:
- Integrated modelling is essential for understanding complex biological systems and their emergent behaviours.
- Holistic understanding necessitates models encompassing major biochemical processes.
- Hybrid modelling methods are key to achieving integrated biological system models.
Purpose of the Study:
- To review popular hybrid modelling methods developed for systems biology.
- To explain the rationale behind these hybrid methods.
- To identify future research directions for integrated biological modelling.
Main Methods:
- Review of existing literature on hybrid modelling techniques.
- Analysis of how hybrid models are constructed from single formalisms.
- Discussion of simulation strategies for hybrid models.
Main Results:
- Identification of currently popular hybrid modelling methods.
- Explanation of the origins and formation of these methods.
- Overview of simulation approaches for hybrid models.
Conclusions:
- Hybrid modelling is crucial for advancing integrated biological system understanding.
- Further research is needed to refine and develop hybrid approaches.
- This review provides a foundation for future work in integrated biological modelling.
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