The simulation approach in synthetic biology

Area of Science:

• * Computational Biology
• * Synthetic Biology
• * Systems Biology

Background:

• * Synthetic biology and systems biology are often perceived as opposing fields: engineering versus understanding, and lab experimentation versus computational modeling.
• * Contemporary biological research faces the challenge of intrinsic biomolecular complexity, including stochasticity and non-linearities.
• * Existing engineering principles for generic objects are insufficient for complex cellular environments.

Purpose of the Study:

• * To demonstrate the convergence of synthetic biology and systems biology through computational techniques.
• * To explore the necessity of advanced computational methods for designing biological parts and devices.
• * To investigate the development of adaptive-generic bio-parts and devices.

Main Methods:

• * Philosophical investigation into the nature of biological parts and devices.
• * Application of simulation-based rational design methods.
• * Analysis of case studies demonstrating in-silico guidance for biological design.

Main Results:

• * Computational techniques are essential for merging synthetic and systems biology.
• * Rational design methods enable the creation of advanced, adaptive bio-parts and devices.
• * Simulation-based approaches improve parameter identification, experimental accuracy, and reduce lab work.

Conclusions:

• * Synthetic and systems biology are increasingly integrated via computational approaches.
• * The development of adaptive-generic bio-parts and devices is a key outcome.
• * This integration facilitates more robust and efficient biological engineering.