Reliability of genetic networks is evolvable
Stefan Braunewell1, Stefan Bornholdt
1Institute for Theoretical Physics, University of Bremen, Bremen, Germany.
Summary
Biological evolution optimizes reliable cell functions from noisy molecular networks. Our study shows that reliable dynamics in stochastic networks are an evolvable trait, achievable through small structural changes.
Area of Science:
- Systems biology
- Evolutionary computation
- Theoretical biology
Background:
- Living cells exhibit reliable functions despite inherent molecular noise.
- This reliability is a key property shaped by biological evolution.
- Understanding the evolvability of reliable dynamics in biological networks is crucial.
Purpose of the Study:
- To investigate the extent to which reliable dynamics in stochastic networks are an evolvable trait.
- To determine if evolutionary algorithms can optimize network reliability.
- To assess the impact of small structural changes on network function.
Main Methods:
- Utilized an evolutionary algorithm with a deterministic selection criterion.
- Focused on the reliability of dynamical attractors in networks.
- Evolved networks composed of noisy discrete threshold nodes.
Main Results:
- Reliable attractor landscapes were frequently achieved from random networks.
- Minimal structural modifications were often sufficient to enhance reliability.
- Networks demonstrated high success rates in evolving towards reliable dynamics while preserving function.
Conclusions:
- The ability to produce reliable dynamics is an evolvable trait in stochastic networks.
- Evolutionary processes can efficiently optimize network reliability.
- Small network alterations can significantly improve functional robustness.
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