Sentence examples for metabolic modeling has from inspiring English sources

Computational metabolic modeling has been applied successfully to gain insight into the metabolism of MTB [ 42– 42].

Constraint-based metabolic modeling has been an important technique to broaden and deepen our knowledge of microbial metabolism and regulation.

Engineered communities have also been useful as a generalized model of cooperation and competition in microbial populations [13], [14] and two-species metabolic modeling has been used in the identification of cooperating variants of E. coli [15].

Over the last decade the field of constraint-based metabolic modeling has witnessed significant progress, which has led to major advances in the modeling, understanding and engineering of different biological systems [ 8- 11].

Yeast has for example been used extensively in biotechnology as a workhorse for production of a wide range of chemicals, and metabolic modeling has helped in many cases to guide the strain construction by finding strategies for improved chemical production [ 10].

Given a completely annotated genome, the challenges in metabolic modeling have been application of appropriate constraints that represent cellular physiology and, thereafter, solving the resulting set of equations.

Since systems biology aims to achieve a quantitative phenotypic description of a biological system, advances in this particular field through the high-throughput analysis of cell parts and genome-scale metabolic modeling have been incorporated in medical and medicinal biotechnology applications.

The stoichiometry metabolic model has been utilized to study the response of cell metabolism to different environmental and genetic perturbations or different stresses caused by inhibitors during lignocellulosic fermentation process (Heer et al. 2009; Hanly and Henson 2014).

Since the first large-scale reconstruction of the Saccharomyces cerevisiae metabolic network 15 years ago the development of yeast metabolic models has progressed rapidly, resulting in no less than nine different yeast genome-scale metabolic models.

The integration of available genomic and metabolomic data through the generation of genome scale metabolic models has enabled the development of computational models that predict the behaviour of organisms under specific conditions and present a route to metabolic engineering.

Generation and curation of plant genome-scale metabolic models has proven far more challenging, not the least of which is our incomplete knowledge of compartmentation and organelle transporters in plants.