scholarly journals Editorial overview: Systems biology: Advances diseases understanding and metabolic engineering

2015 ◽  
Vol 34 ◽  
pp. v-vi ◽  
Author(s):  
Sarah-Maria Fendt ◽  
Costas D Maranas
2018 ◽  
Vol 39 (1) ◽  
pp. 79-98 ◽  
Author(s):  
Arun Kumar Dangi ◽  
Babita Sharma ◽  
Russell T. Hill ◽  
Pratyoosh Shukla

2020 ◽  
Vol 8 (12) ◽  
pp. 1849
Author(s):  
Yujin Jeong ◽  
Sang-Hyeok Cho ◽  
Hookeun Lee ◽  
Hyung-Kyoon Choi ◽  
Dong-Myung Kim ◽  
...  

Cyanobacteria, given their ability to produce various secondary metabolites utilizing solar energy and carbon dioxide, are a potential platform for sustainable production of biochemicals. Until now, conventional metabolic engineering approaches have been applied to various cyanobacterial species for enhanced production of industrially valued compounds, including secondary metabolites and non-natural biochemicals. However, the shortage of understanding of cyanobacterial metabolic and regulatory networks for atmospheric carbon fixation to biochemical production and the lack of available engineering tools limit the potential of cyanobacteria for industrial applications. Recently, to overcome the limitations, synthetic biology tools and systems biology approaches such as genome-scale modeling based on diverse omics data have been applied to cyanobacteria. This review covers the synthetic and systems biology approaches for advanced metabolic engineering of cyanobacteria.


Author(s):  
Ferda Mavituna ◽  
Raul Munoz-Hernandez ◽  
Ana Katerine de Carvalho Lima Lobato

This chapter summarizes the fundamentals of metabolic flux balancing as a computational tool of metabolic engineering and systems biology. It also presents examples from the literature for its applications in medicine. These examples involve mainly liver metabolism and antibiotic production. Metabolic flux balancing is a computational method for the determination of metabolic pathway fluxes through a stoichiometric model of the cellular pathways, using mass balances for intracellular metabolites. It is a powerful tool to study metabolism under normal and abnormal conditions with a view to engineer the metabolism. Its extended potential in medicine is emphasized in the future trends.


Author(s):  
Eberhard O. Voit

Computational models can serve many purposes, but a particularly powerful application of a model is its use as a system simulator. An emerging branch of computational systems biology strives to develop simulators for complex systems in biology and medicine, the premier example being a disease simulator. ‘Simulators’ discusses the nascent efforts towards the development of simulators for practical applications. Disease simulators will deepen our understanding of the physiology of human diseases and their treatment. Simulators in metabolic engineering have the goal of improving the microbial production of bulk materials and of valuable organic compounds. Relatively simple simulators for the production of biofuels and for crop development, such as the Soybean Growth Simulation Model (SoySim), are already in use.


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