title: [Combinatorial optimization of synthetic biological systems].
abstract: A major challenge in synthetic biology is to engineer complex biological systems with novel functions. Due to the inherent complexity of biological systems, it is often difficult to rationally design every component in a synthetic gene network to achive an optimal performance. Combinatorial engineering is an important solution to this problem and can greatly facilitate the construction of novel biological functions. Here, we review methods and techniques developed in recent years for combinatorial optimization of synthetic biological systems, including methods for fine-tuning pathway components, strategies for systematically optimization of metabolic pathways, and techniques for introducing multiplex genome wide perturbations.
authors.affiliation: Department of Biochemical Engineering, School of Chemical Engineering & Technology, Tianjin University, Tianjin 300072, China.
authors.forename: Qun
authors.initials: Q
authors.lastname: Gu
authors.affiliation: Department of Biochemical Engineering, School of Chemical Engineering & Technology, Tianjin University, Tianjin 300072, China.
authors.forename: Yifan
authors.initials: Y
authors.lastname: Li
authors.affiliation: Department of Biochemical Engineering, School of Chemical Engineering & Technology, Tianjin University, Tianjin 300072, China.
authors.forename: Tao
authors.initials: T
authors.lastname: Chen
mesh_terms: D053263:Gene Regulatory Networks; D005818:Genetic Engineering; D060847:Metabolic Engineering / Q000379:methods*; D058615:Synthetic Biology / Q000379:methods*