Computational Approaches in Metabolic Engineering
1Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA
2Department of Chemical Engineering, University of Delaware, Newark, DE, USA
3Department of Biological Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
4Department of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, TN, USA
Computational Approaches in Metabolic Engineering
Description
Organisms can be used to synthesize a wide variety of compounds (such as specialty chemicals, protein therapeutics, small molecule pharmaceuticals and biofuels) with high specificity from a broad range of substrates. Metabolic engineering seeks to optimize the biological production of chemicals by controlling flow through metabolic pathways. This can be achieved through genetic manipulation of the production organism's metabolic or regulatory pathways or by optimizing bioprocessing conditions. Computational models of biological networks can be used to describe metabolic fluxes and/or predict the effects of perturbations (either genetic or environmental) on production. There is a growing interest in using computational tools to help design organisms and bioprocesses that help increasing the production of compounds in biological systems. Computational methods can be used in metabolic engineering applications to guide strain design, evaluate experimental data to suggest further improvements, and design bioprocessing conditions to control production.
The principal focus of this special issue will be on computational approaches in metabolic engineering. We invite authors to submit original research articles and reviews on different topics relating to metabolic engineering, which can range between development of models (e.g., single organism or communities of organisms), methods for strain design, and methods for analysis of experimental datasets (such as gene expression, metabolomic, and proteomic datasets). Potential topics that will be covered include, but are not limited to:
- Advances in metabolic flux analysis
- Metabolic network reconstruction methods
- Regulatory network reconstruction methods
- Development of metabolic models
- Development of regulatory models
- Approaches for analyzing experimental datasets
- Methods for identifying metabolic engineering strategies
- Methods for bioprocess modeling
Before submission authors should carefully read over the journal's Author Guidelines, which are located at http://www.hindawi.com/journals/jbb/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/ according to the following timetable: