Source 1review2020New Phytologist
Toolkit/model-informed rational design
model-informed rational design
Taxonomy: Technique Branch / Method. Workflows sit above the mechanism and technique branches rather than replacing them.
Summary
Model-informed rational design is an engineering method in synthetic biology that uses models to guide the design of biological systems. In the cited plant context, it has been successfully applied to engineering plant gene regulation and metabolism.
Usefulness & Problems
Why this is useful
This method is useful for guiding the engineering of plant biological systems using model-based design logic. The cited source also links broader synthetic biology standardisation and technical advances to increased speed and accuracy of genetic manipulation, which provides context for its utility.
Source:
Recently, this has enabled model-informed rational design to be successfully applied to the engineering of plant gene regulation and metabolism.
Problem solved
Model-informed rational design helps address the challenge of designing plant gene regulatory and metabolic systems in a more informed and systematic manner. The available evidence supports application to plant gene regulation and metabolism, but does not specify particular design bottlenecks or target pathways.
Source:
Recently, this has enabled model-informed rational design to be successfully applied to the engineering of plant gene regulation and metabolism.
Taxonomy & Function
Primary hierarchy
Technique Branch
Method: A concrete method used to build, optimize, or evolve an engineered system.
Mechanisms
No mechanism tags yet.
Techniques
Computational DesignTarget processes
No target processes tagged yet.
Implementation Constraints
The supplied evidence indicates use in plant synthetic biology, specifically for engineering gene regulation and metabolism. No practical details were provided on model type, software framework, experimental workflow, delivery method, or construct design.
The evidence is limited to a high-level statement of successful application in plants. No specific models, quantitative benchmarks, construct architectures, or comparative validations were described in the supplied evidence.
Validation
Cell-freeBacteriaMammalianMouseHumanTherapeuticIndep. Replication
Supporting Sources
Ranked Claims
Model-informed rational design has been successfully applied to engineering plant gene regulation and metabolism.
Recently, this has enabled model-informed rational design to be successfully applied to the engineering of plant gene regulation and metabolism.
Model-informed rational design has been successfully applied to engineering plant gene regulation and metabolism.
Recently, this has enabled model-informed rational design to be successfully applied to the engineering of plant gene regulation and metabolism.
Model-informed rational design has been successfully applied to engineering plant gene regulation and metabolism.
Recently, this has enabled model-informed rational design to be successfully applied to the engineering of plant gene regulation and metabolism.
Model-informed rational design has been successfully applied to engineering plant gene regulation and metabolism.
Recently, this has enabled model-informed rational design to be successfully applied to the engineering of plant gene regulation and metabolism.
Model-informed rational design has been successfully applied to engineering plant gene regulation and metabolism.
Recently, this has enabled model-informed rational design to be successfully applied to the engineering of plant gene regulation and metabolism.
Model-informed rational design has been successfully applied to engineering plant gene regulation and metabolism.
Recently, this has enabled model-informed rational design to be successfully applied to the engineering of plant gene regulation and metabolism.
Model-informed rational design has been successfully applied to engineering plant gene regulation and metabolism.
Recently, this has enabled model-informed rational design to be successfully applied to the engineering of plant gene regulation and metabolism.
Standardisation and key technical advances increased the speed and accuracy of genetic manipulation in synthetic biology.
The application of engineering principles such as standardisation, together with several key technical advances, enabled a revolution in the speed and accuracy of genetic manipulation.
Standardisation and key technical advances increased the speed and accuracy of genetic manipulation in synthetic biology.
The application of engineering principles such as standardisation, together with several key technical advances, enabled a revolution in the speed and accuracy of genetic manipulation.
Standardisation and key technical advances increased the speed and accuracy of genetic manipulation in synthetic biology.
The application of engineering principles such as standardisation, together with several key technical advances, enabled a revolution in the speed and accuracy of genetic manipulation.
Standardisation and key technical advances increased the speed and accuracy of genetic manipulation in synthetic biology.
The application of engineering principles such as standardisation, together with several key technical advances, enabled a revolution in the speed and accuracy of genetic manipulation.
Standardisation and key technical advances increased the speed and accuracy of genetic manipulation in synthetic biology.
The application of engineering principles such as standardisation, together with several key technical advances, enabled a revolution in the speed and accuracy of genetic manipulation.
Standardisation and key technical advances increased the speed and accuracy of genetic manipulation in synthetic biology.
The application of engineering principles such as standardisation, together with several key technical advances, enabled a revolution in the speed and accuracy of genetic manipulation.
Standardisation and key technical advances increased the speed and accuracy of genetic manipulation in synthetic biology.
The application of engineering principles such as standardisation, together with several key technical advances, enabled a revolution in the speed and accuracy of genetic manipulation.
Mathematical and statistical modelling improved the predictability of engineering biological systems despite intrinsic nonlinearity and stochasticity.
Combined with mathematical and statistical modelling, this has improved the predictability of engineering biological systems of which nonlinearity and stochasticity are intrinsic features.
Mathematical and statistical modelling improved the predictability of engineering biological systems despite intrinsic nonlinearity and stochasticity.
Combined with mathematical and statistical modelling, this has improved the predictability of engineering biological systems of which nonlinearity and stochasticity are intrinsic features.
Mathematical and statistical modelling improved the predictability of engineering biological systems despite intrinsic nonlinearity and stochasticity.
Combined with mathematical and statistical modelling, this has improved the predictability of engineering biological systems of which nonlinearity and stochasticity are intrinsic features.
Mathematical and statistical modelling improved the predictability of engineering biological systems despite intrinsic nonlinearity and stochasticity.
Combined with mathematical and statistical modelling, this has improved the predictability of engineering biological systems of which nonlinearity and stochasticity are intrinsic features.
Mathematical and statistical modelling improved the predictability of engineering biological systems despite intrinsic nonlinearity and stochasticity.
Combined with mathematical and statistical modelling, this has improved the predictability of engineering biological systems of which nonlinearity and stochasticity are intrinsic features.
Mathematical and statistical modelling improved the predictability of engineering biological systems despite intrinsic nonlinearity and stochasticity.
Combined with mathematical and statistical modelling, this has improved the predictability of engineering biological systems of which nonlinearity and stochasticity are intrinsic features.
Mathematical and statistical modelling improved the predictability of engineering biological systems despite intrinsic nonlinearity and stochasticity.
Combined with mathematical and statistical modelling, this has improved the predictability of engineering biological systems of which nonlinearity and stochasticity are intrinsic features.
Approval Evidence
1 source1 linked approval claimfirst-pass slug model-informed-rational-design
Recently, this has enabled model-informed rational design to be successfully applied to the engineering of plant gene regulation and metabolism.
Source:
application scopesupports
Model-informed rational design has been successfully applied to engineering plant gene regulation and metabolism.
Recently, this has enabled model-informed rational design to be successfully applied to the engineering of plant gene regulation and metabolism.
Source:
Comparisons
Source-backed strengths
The cited literature states that model-informed rational design has been successfully applied in plants for gene regulation and metabolism engineering. The same source indicates that standardisation and key technical advances increased the speed and accuracy of genetic manipulation in synthetic biology, although performance metrics specific to this method were not provided.
Ranked Citations
- 1.