IGEM:Melbourne/2008/BCModelling/ModelDevelopment

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Strategy

 * connections - this is the first part of the modelling to get the connections right both biologically and theoretically. Jason and Dave are doing this for the linear and binary model respectively. Include as much as possible, remember to employ special cases to be able to simplify the model when necessary and ensure complexity when required.


 * parameters - obtain the right parameters for Hill functions, Kd, degradation rates, RL/RK binding constants, and other parameters for more complex models (such as [REFshae 1985|shae 1985], statisical mechanics model for promoter activity)


 * break apart - need to obtain realistic and desired output for each bit of the binary or each component of the linear model.
 * To assist the individual circuits are to be 'broken down' into smaller section that will be have parameters adjusted such that they behave in two deisred fashions: ideal (as close to square-wave as possible) and real not changing the estimated parameters.


 * iterate to optimize results...

Initial Model Assumptions

 * (refer to arkin 1998(REF) paper here ...
 * deterministic chemical kinetics
 * inital concentrations of intermediates at 0
 * only model chemical interactions and focus on transcriptional control, ignoring post-transcriptional control mechanisms and characterise protein production as a continuous process.
 * activator/repressor binding events to individual promoters are the rate-limiting steps in gene expression (total wrong ... but needed at first ... can modify hill function parameters to suit)

Initial Conditions, IC
(conduct in parallel with overall sensitivity analysis)

Strategy

 * model leaky transcription
 * group components in boxes ... that have similar behaviour and approximate initial concentrations ...
 * recalibrate as necessary
 * conduct a sensitivity analysis on the inital conditions and optimize accordingly.
 * senstivities of SS concentrations to change in initial conditions of various parameters.
 * sensitvities of transient output to changes in initial condtions ... but then assume that system first settle at SS .. so this might be irrelevant ... have to decide this KEY point ... is systems at SS or do we start at artifical point ... and go for a couple of cycles
 * introduce further leaky transcriptions via beta'z parameters in hill functions ...
 * iterate

Changing Model Assumptions

 * leaky transcription/expression
 * start point ... artificial or SS

Sensitivity Analysis, SA
(conduction in parallel with IC study)

Strategy

 * basic sensitivity analysis of 1 variable perturbations with no other input
 * SA of 1 variable perturbations in addition to pulsatile signal
 * grading of output ... refer to previous work (ie. L=A/B+A ... remember dave/jason)

Stochastic Analsyis, StA
(if we get time)

Strategy

 * read arkin review
 * impelement stochastic ode
 * implement model of other stages
 * operator/promoter binding
 * control of transcription initiation
 * transcription
 * termination
 * antitermination
 * translation
 * protein interaction
 * protein degradation