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A Critical Comparison of Rejection-Based Algorithms for Simulation of Large Biochemical Reaction Networks.
1Department of Computer Science, Aalto University, Espoo, Finland. thanh.vo@aalto.fi.
Bulletin of Mathematical Biology
|July 8, 2018
Summary
We compared two simulation methods, the composition-rejection algorithm (SSA-CR) and rejection-based SSA (RSSA), for large biological reaction networks. SSA-CR is faster for expensive search costs, while RSSA excels when update costs dominate.
Area of Science:
- Computational biology
- Biochemical systems analysis
- Algorithm development
Background:
- Stochastic simulation algorithm (SSA) is crucial for understanding biological systems.
- Simulating large reaction networks requires computationally efficient methods.
- Rejection-based techniques enhance SSA's performance.
Purpose of the Study:
- Compare the efficiency of two rejection-based SSA methods: SSA-CR and RSSA.
- Provide a clear interpretation of rejection-based techniques in SSA.
- Guide informed choices for simulating biochemical networks.
Main Methods:
- Theoretical analysis of SSA-CR and RSSA.
- Runtime comparison on biological models.
- Evaluation of computational costs (search vs. update).
Main Results:
- SSA-CR is more efficient for networks with high search costs.
- RSSA is more efficient for networks with dominant update costs.
- Identified key factors influencing algorithm performance.
Conclusions:
- The choice between SSA-CR and RSSA depends on network characteristics.
- RSSA is often preferred in practice due to dominant update costs.
- Accurate interpretation of rejection-based methods is vital for efficient simulation.
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