# Application of combinatorial optimization strategies in synthetic biology

Review · Gita Naseri, Mattheos A. G. Koffas

- Archive id: doi:10.1038/s41467-020-16175-y
- Published: 2020-05-15
- Venue: Nature Communications
- DOI: https://doi.org/10.1038/s41467-020-16175-y
- PMID: 32415065
- Citations: 187
- Source URL: https://doi.org/10.1038/s41467-020-16175-y
- PDF: https://www.nature.com/articles/s41467-020-16175-y.pdf
- Provenance: openalex

## Abstract

In the first wave of synthetic biology, genetic elements, combined into simple circuits, are used to control individual cellular functions. In the second wave of synthetic biology, the simple circuits, combined into complex circuits, form systems-level functions. However, efforts to construct complex circuits are often impeded by our limited knowledge of the optimal combination of individual circuits. For example, a fundamental question in most metabolic engineering projects is the optimal level of enzymes for maximizing the output. To address this point, combinatorial optimization approaches have been established, allowing automatic optimization without prior knowledge of the best combination of expression levels of individual genes. This review focuses on current combinatorial optimization methods and emerging technologies facilitating their applications.

_Abstract reproduced under CC-BY (publisher license, via OpenAlex)._

Topics: [Synthetic Biology & Genome Engineering](https://space-kitty.com/topics/synthetic-biology)

---
Space Kitty Archive · https://space-kitty.com · API: https://space-kitty.com/api/v1 · MCP: https://space-kitty.com/mcp · Premium: $0.20/request via x402 (Base Sepolia (testnet)). Metadata: arXiv (CC0), OpenAlex (CC0), Europe PMC (CC BY/CC0 works), ClinicalTrials.gov.
