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Genome scale modeling in systems biology: algorithms and resources
Ali Najafi1, Gholamreza Bidkhori1, Joseph H Bozorgmehr1
1Laboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and Biophysics, University of Tehran, Iran;
This review explores computational modeling and network analysis for understanding complex biological systems. It details algorithms, tools, and standards for simulating and analyzing cellular networks, aiding researchers in quantitative biological insights.
Area of Science:
- Systems Biology
- Computational Biology
- Bioinformatics
Background:
- Experimental procedures are increasingly complemented by in silico studies and simulations.
- Biological networks serve as platforms for integrating diverse experimental data for system analysis.
- Understanding complex cellular dynamics necessitates quantitative approaches beyond traditional experimental methods.
Purpose of the Study:
- To review popular modeling algorithms, tools, and standards for biological network analysis.
- To provide an accessible overview of processes for modeling and simulating biological networks.
- To illustrate concepts with examples, images, and graphs for diverse scientific backgrounds.
Main Methods:
- Network analysis approaches for quantitative modeling of biological systems.
- Review of popular algorithms and tools for representing, simulating, and analyzing cellular networks.
- Integration of analytical experimental approaches with computational models.
Main Results:
- Highlights key modeling algorithms, tools, and emerging standards for cellular network analysis.
- Provides a framework for understanding biological network modeling and simulation processes.
- Demonstrates concepts through examples and visualizations.
Conclusions:
- Systems biology aims for holistic understanding through integrated experimental and computational approaches.
- Computational modeling and simulation are crucial for deciphering complex cellular dynamics.
- The review offers a guide for researchers in biological and mathematical fields to engage with network analysis.
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