title: Metabolic systems modeling for cell factories improvement.
abstract: Techniques for modeling microbial bioproduction systems have evolved over many decades. Here, we survey recent literature and focus on modeling approaches for improving bioproduction. These techniques from systems biology are based on different methodologies, starting from stoichiometry only to various stoichiometry with kinetics approaches that address different issues in metabolic systems. Techniques to overcome unknown kinetic parameters using random sampling have emerged to address meaningful questions. Among those questions, pathway robustness seems to be an important issue for metabolic engineering. We also discuss the increasing significance of databases in biology and their potential impact for biotechnology.
authors.affiliation: Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, Los Angeles, CA 90095, United States.
authors.forename: Po-Wei
authors.initials: PW
authors.lastname: Chen
authors.affiliation: Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, Los Angeles, CA 90095, United States.
authors.forename: Matthew K
authors.initials: MK
authors.lastname: Theisen
authors.affiliation: Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, Los Angeles, CA 90095, United States; Academia Sinica, Taipei 11529, Taiwan. Electronic address: liaoj@ucla.edu.
authors.forename: James C
authors.initials: JC
authors.lastname: Liao
mesh_terms: D002477:Cells / Q000378:metabolism*; D007700:Kinetics; D060847:Metabolic Engineering / Q000379:methods*; D064688:Metabolic Flux Analysis; D008954:Models, Biological; D049490:Systems Biology / Q000379:methods*