Team:Purdue/Modeling

From 2012.igem.org

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<h2> Equations </h2>
<h2> Equations </h2>
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<h5> The growth of the Biofilm can be modeled with modified continuous growth models. Traditional models of population growth make use of basic differential equations to measure the change in population over unit time. At the most fundamental level <p>
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<h5> The growth of the Biofilm can be modeled with modified continuous growth models. Traditional models of population growth make use of basic differential equations to measure the change in population over unit time. At the most fundamental level
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Where r is the positive rate of growth, K is the positive carrying capacity of the environment, and N is the population level. This equation will eventually run to one of two steady state equilibria as the population either (A) approaches its carrying capacity [N = K] or runs to extinction [N=0].
Where r is the positive rate of growth, K is the positive carrying capacity of the environment, and N is the population level. This equation will eventually run to one of two steady state equilibria as the population either (A) approaches its carrying capacity [N = K] or runs to extinction [N=0].
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To understand the dynamics of the biofilm during growth, we treat the bacterial attachment and detachment as a reversible reaction of the form
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            Bacteria Attached  <
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            <i>k<sub>1</sub></i>
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              >  Bacteria Detached
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            <i>k<sub>2</sub></i>
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Revision as of 19:00, 13 July 2012


Modeling

Levels of Investigation

  • How biofilm responds to shear, flow, temp, surface attachment, etc
  • How Silica traps the particle during flow
  • How Curli adheres and how OmpA-Silicatein Alpha polymerizes Silica/How the silica crystalizes (introduction of Salicylic Acid)
  • How protien expression responds to external and metabolic variation (e.g. introduction of IPTG to system)
  • How constructs work with each other/controls systems
  • How RBS/ Promoter effects protein expression

Distribution of Modeling

Matlab
  • Protein Production
  • Feed Forward Loop Control Structure
TinkerCell
  • Quorum sensing
  • Feed Forward Loop
JMP
  • Experimental Design and Characterization Experiments
Comsol/Other
  • Waterflow and shear force on final system
  • Silica formation

Design

  • Desired Outcomes of Models
  • Levels of Abstractions
    • Biofilter response to Environmental conditions
      • Shear
      • Flow
      • Temperature
      • Abiotic Surface (Adhesion)
    • Formation of Silica Matrix
    • BioFilm Development
      • Model of Bacterial Growth, Death, Breaking Off
    • Expression of Proteins
      • Response to addition of IPTG
      • Optimal Production rate/expression of Curli and OmpA-Silicatein Alpha protiens
      • Control Systems
      • Fine Tuning of Protein Expression with RBS/Promoter combination variants
  • Platforms
  • Considerations and Assumption
  • Parameters

Equations

    The growth of the Biofilm can be modeled with modified continuous growth models. Traditional models of population growth make use of basic differential equations to measure the change in population over unit time. At the most fundamental level

    Population Change Rate = dN = rN(1-N/K)
    dt

    Where r is the positive rate of growth, K is the positive carrying capacity of the environment, and N is the population level. This equation will eventually run to one of two steady state equilibria as the population either (A) approaches its carrying capacity [N = K] or runs to extinction [N=0].

    To understand the dynamics of the biofilm during growth, we treat the bacterial attachment and detachment as a reversible reaction of the form

    Bacteria Attached < k1 > Bacteria Detached
    k2

Outcomes

Parameter Theoretical Value Experimental Value Analysis
Parameter 1 ____ ____ ____
Parameter 2 ____ ____ ____
Parameter 3 ____ ____ ____
Parameter 4 ____ ____ ____

References

Retrieved from "http://2012.igem.org/Team:Purdue/Modeling"