Biology Reference
In-Depth Information
transcriptional circuits. Some have been packaged into downloadable software tools.
Common to most of the methods developed so far is the use of ordinary differential
equations (ODEs) to model the dynamics of the system (though some can also handle
stochastic dynamics). These computational methods differ in how the networks are
parameterized, how the dynamics are approximated, and how the optimization is
formulated.
The Genetdes method attempts to design optimal transcriptional networks and kinetic
parameters with targeted behaviors.
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The optimization is performed using simulated
annealing with moves in the model space including synthetic genes and regulatory
interactions, and the change of kinetic parameters. The Robust Verification of Gene
Networks (RoVerGeNe) method inputs an existing network and generates a set of
constraints to express the desired behavior of the network.
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Approximating the regulation
terms in the dynamical equations using piecewise linear functions, the analysis of the
network becomes more efficient compared to a full nonlinear ODE model. The Linear
Temporal Logic (LTL) is used to express the desired network behavior, and RoVerGeNe
uses abstraction and model checking for a given set of parameters to determine whether
the parameters are able to satisfy the constraints of the desired behavior. If the parameters
are valid for the given constraints, then a specific set of parameters are selected to
represent the specified behavior. The MATLAB code for RoVerGeNe is available online
(
Table 8.1
).
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The OptCircuit method uses multiple sources of literature on promoters, protein molecules,
and inducers.
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By doing so, systems are constructed to maximize an objective function
derived from the desired dynamics. Here the full dynamics is approximated under the
assumption that fast reactions (rate constants on the order of seconds) are in
pseudoequilibrium. The optimization is formulated as a mixed integer dynamic
optimization problem and can be applied to both system topology and kinetic parameters.
This method has been used to design a toggle switch, a genetic decoder, and a concentration
band detector.
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A different approach is to develop languages that can be compiled into sequences of
standard biological parts. The Genetic Engineering of living Cells (GEC) method is an
elaborate approach that allows the expression of logical interactions between biological
parts using a programming language.
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The language can also serve as an explicit proposal
and to guide the emerging standard of biological parts which so far has been related to
biological, rather than logical, properties of parts.
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GenoCAD is an example of a context-
free grammar that enforces a set of production rules that ensure that the user will produce
a biologically valid construct.
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GenoCAD is a web-based tool used to design artificial
genes, protein expression vectors, and genetic networks composed of multiple functional
genetic parts.
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By using simple GUI, complex constructs composed of dozens of
functional blocks can be designed within minutes. It also provides the genetic sequence of
the construct designed from its comprehensive libraries of genetic parts. SynBioSS Designer
is another web-based tool available for the design of DNA constructs.
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With the input of
the molecular parts involved in gene expression and regulation, SynBioSS Designer
automatically generates a complete network of biomolecular reactions as output.
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GUI enables convenient construction of a genetic circuit by dragging and dropping
components on a canvas.
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BioJADE was the first genetic circuit tool using GUI, and
interactively utilizes the BioBrick collection.
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Using the GUI, BioJADE allows designers to
specify the circuit, tune it, and perform simulations of the circuit behaviors. It also provides
connections between databases and simulations of the designed circuits through the
Distributed Flexible and User eXtensible (D-FLUX) protocol. One of the standard simulators
in D-FLUX is TABASCO, which performs genome-scale simulation of transcription and
translation in the cell at the molecular and single base pair level.
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