ReviewJournal of the Royal Society, Interface2016
Synthetic biology and regulatory networks: where metabolic systems biology meets control engineering.
Review in Journal of the Royal Society, Interface, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed.
- Snapshot at Saccharomycopsis fibuligera metabolism for industrial terpenoid production and bioengineering.BMC microbiology · 2026Article
- Multimodal learning reveals plants' hidden sensory integration logic.BMC genomics · 2026Article
- Engineered strains as living factories: efficient biosynthesis and modification of natural products via synthetic biology and one-pot chemical tandem reactions.Frontiers in microbiology · 2026Review
- Key Technologies of Synthetic Biology in Industrial Microbiology.Microorganisms · 2025Review
- Metabolic Remodeling of the Tricarboxylic Acid Cycle and Glycolysis Reveals Cold-Induced Respiratory Adaptations inInsects · 2025Article
- Engineering principles for rationally design therapeutic strategies against hepatocellular carcinoma.Frontiers in molecular biosciences · 2024Review
- Technologies for whole-cell modeling: Genome-wide reconstruction of a cell in silico.Development, growth & differentiation · 2023Review
- An enhanced transcription factor repressilator that buffers stochasticity and entrains to an erratic external circadian signal.Frontiers in systems biology · 2023Article
- Quantitative metabolic fluxes regulated by trans-omic networks.The Biochemical journal · 2022Review
- Harnessing Interactional Sensory Genes for Rationally Reprogramming Chaotic Metabolism.Research (Washington, D.C.) · 2022Article
- Implementation and acceleration of optimal control for systems biology.Journal of the Royal Society, Interface · 2021Review
- Microbial redemption of "evil" days: a global appraisal to food security.Journal of food science and technology · 2021Review
- Programmable gene regulation for metabolic engineering using decoy transcription factor binding sites.Nucleic acids research · 2021Article
- Dynamic control in metabolic engineering: Theories, tools, and applications.Metabolic engineering · 2021Review
- ROS networks: designs, aging, Parkinson's disease and precision therapies.NPJ systems biology and applications · 2020Article
- Using optimal control to understand complex metabolic pathways.BMC bioinformatics · 2020Article
- Quantifying Dynamic Regulation in Metabolic Pathways with Nonparametric Flux Inference.Biophysical journal · 2019Article
- Adaptive information processing of network modules to dynamic and spatial stimuli.BMC systems biology · 2019Article
- Yeast Systems Biology: The Continuing Challenge of Eukaryotic Complexity.Methods in molecular biology (Clifton, N.J.) · 2019Article
- Genome-Scale Architecture of Small Molecule Regulatory Networks and the Fundamental Trade-Off between Regulation and Enzymatic Activity.Cell reports · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Metabolic pathways can be engineered to maximize the synthesis of various products of interest. With the advent of computational systems biology, this endeavour is usually carried out through in silico theoretical studies with the aim to guide and complement further in vitro and in vivo experimental efforts. Clearly, what counts is the result in vivo, not only in terms of maximal productivity but also robustness against environmental perturbations. Engineering an organism towards an increased production flux, however, often compromises that robustness. In this contribution, we review and investigate how various analytical approaches used in metabolic engineering and synthetic biology are related to concepts developed by systems and control engineering. While trade-offs between production optimality and cellular robustness have already been studied diagnostically and statically, the dynamics also matter. Integration of the dynamic design aspects of control engineering with the more diagnostic aspects of metabolic, hierarchical control and regulation analysis is leading to the new, conceptual and operational framework required for the design of robust and productive dynamic pathways.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.