Predicting genetic modification targets based on metabolic network analysis--a review / 生物工程学报
Chinese Journal of Biotechnology
; (12): 1-13, 2016.
Artigo
em Chinês
| WPRIM (Pacífico Ocidental)
| ID: wpr-337404
Biblioteca responsável:
WPRO
ABSTRACT
Construction of artificial cell factory to produce specific compounds of interest needs wild strain to be genetically engineered. In recent years, with the reconstruction of many genome-scale metabolic networks, a number of methods have been proposed based on metabolic network analysis for predicting genetic modification targets that lead to overproduction of compounds of interest. These approaches use constraints of stoichiometry and reaction reversibility in genome-scale models of metabolism and adopt different mathematical algorithms to predict modification targets, and thus can discover new targets that are difficult to find through traditional intuitive methods. In this review, we introduce the principle, merit, demerit and application of various strain optimization methods in detail. The main problems in existing methods and perspectives on this emerging research field are also discussed, aiming to provide guidance to choose the appropriate methods according to different types of products and the reliability of the predicted results.
Texto completo:
Disponível
Base de dados:
WPRIM (Pacífico Ocidental)
Assunto principal:
Algoritmos
/
Biotecnologia
/
Simulação por Computador
/
Microbiologia Industrial
/
Reprodutibilidade dos Testes
/
Genoma
/
Redes e Vias Metabólicas
/
Engenharia Metabólica
/
Métodos
/
Modelos Teóricos
Tipo de estudo:
Estudo prognóstico
Idioma:
Chinês
Revista:
Chinese Journal of Biotechnology
Ano de publicação:
2016
Tipo de documento:
Artigo