Difference between revisions of "Team:HokkaidoU Japan/Modeling"

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<h2> Modeling</h2>
 
<h2> Modeling</h2>
  
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<p>If amount of antimicrobial peptides (here referred to as A) bacteria cell produce is increased, conversely the number of host cells (referred to as N) will be decreased because of toxicity of the peptide. We want to express this relation as model.</p>
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<p>First, we want to describe the number of host cells growing without toxicity of the peptide as the differential equation. The logistic equation is a model of population growth first published by Pierre Verhulst. The logistic model is described by the differential equation (figure.1)</p>
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<p>where r is rate of maximum population growth and K is carrying capacity. Dividing both sides by K and defining b=N/K then gives the differential equation</p><br>
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<P>Next, we add the term of toxicity of the antimicrobial peptide to this equation and we describe amount of antimicrobial peptides in the second differential equation (figure.2)</p>
  
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<p>where c is rate of toxicity of the antimicrobial peptide, d is rate of expression of the antimicrobial peptide e is rate of decomposition of the antimicrobial peptide</p><br>
<h4>Note</h4>
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<p>Here, we took 1 for 3 constants (a, b, c) of the right side in the first formula using the flexibilities of the scale. Though here we let parameter e value be 1 arbitarily, this value does not affect qualitatively as the formula shows. We find the graph above by regarding this formula as a function of parameter d.</p>
<p>In order to be considered for the <a href="https://2015.igem.org/Judging/Awards#SpecialPrizes">Best Model award</a>, you must fill out this page.</p>
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<p>Mathematical models and computer simulations provide a great way to describe the function and operation of BioBrick Parts and Devices. Synthetic Biology is an engineering discipline, and part of engineering is simulation and modeling to determine the behavior of your design before you build it. Designing and simulating can be iterated many times in a computer before moving to the lab. This award is for teams who build a model of their system and use it to inform system design or simulate expected behavior in conjunction with experiments in the wetlab.</p>
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Here are a few examples from previous teams:
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<ul>
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<li><a href="https://2014.igem.org/Team:ETH_Zurich/modeling/overview">ETH Zurich 2014</a></li>
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<li><a href="https://2014.igem.org/Team:Waterloo/Math_Book">Waterloo 2014</a></li>
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</ul>
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<p style="text-align:left; float:left;">
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<a href="https://2015.igem.org/Team:HokkaidoU_Japan/alpha-defensin">←Alpha-Defensin Non-commensal Bacteria Killing System</a>
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</p>
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<p style="text-align:right;">
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<a href="https://2015.igem.org/Team:HokkaidoU_Japan">Back to Top→</a>
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Revision as of 03:08, 16 September 2015

Modeling

Modeling

If amount of antimicrobial peptides (here referred to as A) bacteria cell produce is increased, conversely the number of host cells (referred to as N) will be decreased because of toxicity of the peptide. We want to express this relation as model.

First, we want to describe the number of host cells growing without toxicity of the peptide as the differential equation. The logistic equation is a model of population growth first published by Pierre Verhulst. The logistic model is described by the differential equation (figure.1)

where r is rate of maximum population growth and K is carrying capacity. Dividing both sides by K and defining b=N/K then gives the differential equation


Next, we add the term of toxicity of the antimicrobial peptide to this equation and we describe amount of antimicrobial peptides in the second differential equation (figure.2)

where c is rate of toxicity of the antimicrobial peptide, d is rate of expression of the antimicrobial peptide e is rate of decomposition of the antimicrobial peptide


Here, we took 1 for 3 constants (a, b, c) of the right side in the first formula using the flexibilities of the scale. Though here we let parameter e value be 1 arbitarily, this value does not affect qualitatively as the formula shows. We find the graph above by regarding this formula as a function of parameter d.

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