Toolkit/model-informed rational design

model-informed rational design

Engineering Method·Research·Since 2020

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.

Target processes

No target processes tagged yet.

Implementation Constraints

cofactor dependency: cofactor requirement unknownencoding mode: genetically encodedimplementation constraint: context specific validationoperating role: builder

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

Claim 1application scopesupports2020Source 1needs review

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.
Claim 2application scopesupports2020Source 1needs review

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.
Claim 3application scopesupports2020Source 1needs review

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.
Claim 4application scopesupports2020Source 1needs review

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.
Claim 5application scopesupports2020Source 1needs review

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.
Claim 6application scopesupports2020Source 1needs review

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.
Claim 7application scopesupports2020Source 1needs review

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.
Claim 8application scopesupports2020Source 1needs review

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.
Claim 9application scopesupports2020Source 1needs review

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.
Claim 10application scopesupports2020Source 1needs review

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.
Claim 11application scopesupports2020Source 1needs review

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.
Claim 12application scopesupports2020Source 1needs review

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.
Claim 13application scopesupports2020Source 1needs review

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.
Claim 14application scopesupports2020Source 1needs review

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.
Claim 15application scopesupports2020Source 1needs review

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.
Claim 16application scopesupports2020Source 1needs review

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.
Claim 17application scopesupports2020Source 1needs review

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.
Claim 18application scopesupports2020Source 1needs review

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.
Claim 19application scopesupports2020Source 1needs review

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.
Claim 20application scopesupports2020Source 1needs review

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.
Claim 21application scopesupports2020Source 1needs review

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.
Claim 22application scopesupports2020Source 1needs review

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.
Claim 23application scopesupports2020Source 1needs review

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.
Claim 24application scopesupports2020Source 1needs review

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.
Claim 25application scopesupports2020Source 1needs review

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.
Claim 26application scopesupports2020Source 1needs review

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.
Claim 27application scopesupports2020Source 1needs review

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.
Claim 28methodological impactsupports2020Source 1needs review

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.
Claim 29methodological impactsupports2020Source 1needs review

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.
Claim 30methodological impactsupports2020Source 1needs review

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.
Claim 31methodological impactsupports2020Source 1needs review

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.
Claim 32methodological impactsupports2020Source 1needs review

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.
Claim 33methodological impactsupports2020Source 1needs review

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.
Claim 34methodological impactsupports2020Source 1needs review

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.
Claim 35methodological impactsupports2020Source 1needs review

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.
Claim 36methodological impactsupports2020Source 1needs review

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.
Claim 37methodological impactsupports2020Source 1needs review

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.
Claim 38methodological impactsupports2020Source 1needs review

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.
Claim 39methodological impactsupports2020Source 1needs review

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.
Claim 40methodological impactsupports2020Source 1needs review

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.
Claim 41methodological impactsupports2020Source 1needs review

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.
Claim 42methodological impactsupports2020Source 1needs review

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.
Claim 43methodological impactsupports2020Source 1needs review

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.
Claim 44methodological impactsupports2020Source 1needs review

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.
Claim 45methodological impactsupports2020Source 1needs review

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.
Claim 46methodological impactsupports2020Source 1needs review

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.
Claim 47methodological impactsupports2020Source 1needs review

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.
Claim 48predictability improvementsupports2020Source 1needs review

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.
Claim 49predictability improvementsupports2020Source 1needs review

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.
Claim 50predictability improvementsupports2020Source 1needs review

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.
Claim 51predictability improvementsupports2020Source 1needs review

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.
Claim 52predictability improvementsupports2020Source 1needs review

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.
Claim 53predictability improvementsupports2020Source 1needs review

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.
Claim 54predictability improvementsupports2020Source 1needs review

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.
Claim 55predictability improvementsupports2020Source 1needs review

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.
Claim 56predictability improvementsupports2020Source 1needs review

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.
Claim 57predictability improvementsupports2020Source 1needs review

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.
Claim 58predictability improvementsupports2020Source 1needs review

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.
Claim 59predictability improvementsupports2020Source 1needs review

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.
Claim 60predictability improvementsupports2020Source 1needs review

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.
Claim 61predictability improvementsupports2020Source 1needs review

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.
Claim 62predictability improvementsupports2020Source 1needs review

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.
Claim 63predictability improvementsupports2020Source 1needs review

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.
Claim 64predictability improvementsupports2020Source 1needs review

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.
Claim 65predictability improvementsupports2020Source 1needs review

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.
Claim 66predictability improvementsupports2020Source 1needs review

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.
Claim 67predictability improvementsupports2020Source 1needs review

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.

Compared with CoTV

model-informed rational design and CoTV address a similar problem space.

Shared frame: same top-level item type

Strengths here: looks easier to implement in practice.

Compared with genome engineering

model-informed rational design and genome engineering address a similar problem space.

Shared frame: same top-level item type

model-informed rational design and light-dependent protein (un)folding reactions address a similar problem space.

Shared frame: same top-level item type

Strengths here: looks easier to implement in practice.

Ranked Citations

  1. 1.
    StructuralSource 1New Phytologist2020Claim 22Claim 21Claim 21

    Seeded from load plan for claim cl2. Extracted from this source document.