ReviewMetabolic engineering communications2015
Co-evolution of strain design methods based on flux balance and elementary mode analysis.
Review in Metabolic engineering communications, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 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
26 citing papers in PubMed.
- Minimal cut sets in metabolic networks: from conceptual foundations to applications in metabolic engineering and biomedicine.Briefings in bioinformatics · 2025Review
- CFSA: Comparative flux sampling analysis as a guide for strain design.Metabolic engineering communications · 2024Article
- A kinetic framework for modeling oleochemical biosynthesis in Escherichia coli.Biotechnology and bioengineering · 2022Article
- Engineering the glyoxylate cycle for chemical bioproduction.Frontiers in bioengineering and biotechnology · 2022Review
- Metabolic modelling approaches for describing and engineering microbial communities.Computational and structural biotechnology journal · 2021Review
- Opportunities and Challenges for Microbial Synthesis of Fatty Acid-Derived Chemicals (FACs).Frontiers in bioengineering and biotechnology · 2021Review
- Genome-scale metabolic rewiring improves titers rates and yields of the non-native product indigoidine at scale.Nature communications · 2020Article
- Simulating the evolutionary trajectories of metabolic pathways for insect symbionts in the genusMicrobial genomics · 2020Article
- Machine and deep learning meet genome-scale metabolic modeling.PLoS computational biology · 2019Review
- Comparison of pathway analysis and constraint-based methods for cell factory design.BMC bioinformatics · 2019Article
- Article
- Identification of growth-coupled production strains considering protein costs and kinetic variability.Metabolic engineering communications · 2018Article
- In silico model-guided identification of transcriptional regulator targets for efficient strain design.Microbial cell factories · 2018Article
- Fast automated reconstruction of genome-scale metabolic models for microbial species and communities.Nucleic acids research · 2018Article
- Review
- A mathematical framework for yield (vs. rate) optimization in constraint-based modeling and applications in metabolic engineering.Metabolic engineering · 2018Article
- Constraint-based modeling in microbial food biotechnology.Biochemical Society transactions · 2018Review
- OptPipe - a pipeline for optimizing metabolic engineering targets.BMC systems biology · 2017Article
- Growth-coupled overproduction is feasible for almost all metabolites in five major production organisms.Nature communications · 2017Article
- Redesigning metabolism based on orthogonality principles.Nature communications · 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
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
More than a decade ago, the first genome-scale metabolic models for two of the most relevant microbes for biotechnology applications,
Indexed as
Identifiers
What OpenQuestion holds
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.