title: Improving prediction fidelity of cellular metabolism with kinetic descriptions.
abstract: Several modeling frameworks for describing and redirecting cellular metabolism have been developed keeping pace with the rapid development in high-throughput data generation and advances in metabolic engineering techniques. The incorporation of kinetic information within stoichiometry-only modeling techniques offers potential advantages for improved phenotype prediction and consequently more precise computational strain design. In addition to substrate-level kinetic regulatory information, the integration of a number of additional layers of regulation at the transcription, translation, and post-translation levels is sought after by many research groups. However, the practical integration of these complex biological processes into a unified framework amenable to design remains an ongoing challenge.
authors: Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, United States.
authors: Anupam
authors: A
authors: Chowdhury
authors: Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, United States.
authors: Ali
authors: A
authors: Khodayari
authors: Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, United States. Electronic address: costas@psu.edu.
authors: Costas D
authors: CD
authors: Maranas
mesh_terms: D007700:Kinetics; D060847:Metabolic Engineering / Q000379:methods*; D008954:Models, Biological; D010641:Phenotype