Computational modelling of genome-scale metabolic networks and its application to CHO cell cultures.
Comput Biol Med
; 88: 150-160, 2017 09 01.
Article
de En
| MEDLINE
| ID: mdl-28732234
ABSTRACT
Genome-scale metabolic models (GEMs) have become increasingly important in recent years. Currently, GEMs are the most accurate in silico representation of the genotype-phenotype link. They allow us to study complex networks from the systems perspective. Their application may drastically reduce the amount of experimental and clinical work, improve diagnostic tools and increase our understanding of complex biological phenomena. GEMs have also demonstrated high potential for the optimisation of bio-based production of recombinant proteins. Herein, we review the basic concepts, methods, resources and software tools used for the reconstruction and application of GEMs. We overview the evolution of the modelling efforts devoted to the metabolism of Chinese Hamster Ovary (CHO) cells. We present a case study on CHO cell metabolism under different amino acid depletions. This leads us to the identification of the most influential as well as essential amino acids in selected CHO cell lines.
Mots clés
Texte intégral:
1
Collection:
01-internacional
Base de données:
MEDLINE
Sujet principal:
Biologie informatique
/
Voies et réseaux métaboliques
/
Analyse des flux métaboliques
/
Modèles biologiques
Type d'étude:
Prognostic_studies
Limites:
Animals
Langue:
En
Journal:
Comput Biol Med
Année:
2017
Type de document:
Article
Pays d'affiliation:
Slovénie