Difference between revisions of "Team:Groningen/Model"

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<article>
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<section>
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<section>
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<h2>Modelling</h2>
  
−
<p>During the CryptoGErM project we came across several problems and questions that we could not solve in the lab. Therefore we made use of several different modelling approaches. Using artificial intelligence, mathematical models and protein-DNA interaction models we could draw essential conclusions for our project.</p>
+
<p>During the CryptoGErM project we came across several problems and  
 +
questions that we could not solve in the lab. Therefore we made use of  
 +
several different modelling approaches. Using artificial intelligence,  
 +
mathematical models and protein-DNA interaction models we could draw  
 +
essential conclusions for our project.</p>
 +
</section>
  
−
</section>
+
<section>
 +
<div class="split">
 +
<div class="left fltwo">
 +
<h3>Belief-Desire-Intention Model</h3>
 +
 +
<p>We asked ourselves what happens if someone tries to hack our
 +
system (see photo). How would this person behave? Using an
 +
artificial intelligence (AI) model, we explored the behaviour
 +
of the people who use, or try to abuse, the CryptoGErM system.
 +
The people are modelled in a multi-agent simulation using
 +
genetic algorithms. This model helps us to predict the and
 +
intentions of the users and intruders of our system.</p>
 +
 +
<ul>
 +
<li><a href="/Team:Groningen/AIModel">Read more about the AI model.</a></li>
 +
</ul>
 +
</div>
  
 +
<div class="right flone cycler">
 +
<img src="https://static.igem.org/mediawiki/2016/c/cc/T--Groningen---modelling---hacker-.jpeg" />
 +
<img class="active base" src="https://static.igem.org/mediawiki/2016/b/b4/T--Groningen---modelling---MatthiaBDI-.jpeg" />
 +
</div>
 +
</div>
 +
</section>
  
−
<h2>Belief-Desire-Intention Model</h2>
+
<section>
−
<section>
+
<div class="split">
−
<p>
+
<div class="right fltwo">
 +
<h3>Random mutations in <em>Bacillus subtilis</em> </h3>
 +
 +
<p>We realized a random mutation would be unpleasant (see
 +
photo) in our CryptoGErM project. The data stored in the
 +
CryptoGErM system might be endangered by random mutations in
 +
the DNA. This article contains research of the literature on
 +
known mutation rates of <em>B. subtilis</em> under the special
 +
conditions and treatments that will be applied.</p>
  
−
<div class="split"><div class="left fltwo">We asked ourselves what happens if someone tries to hack our system (see photo). How would this person behave? Using an artificial intelligence (AI) model, we explored the behaviour of the people who use, or try to abuse, the CryptoGErM system. The people are modelled in a multi-agent simulation using genetic algorithms. This model helps us to predict the and intentions of the users and intruders of our system.
+
<ul>
 +
<li><a href="/Team:Groningen/MutationRates">Read more about the <em>Bacillus subtilis</em> mutation rates.</a></li>
 +
</ul>
 +
</div>
 +
<div class="left flone">
 +
<img src="https://static.igem.org/mediawiki/2016/1/11/T--Groningen---modelling---eikemutation-.jpeg" />
 +
</div>
 +
</div>
 +
</section>
  
−
<p><ul><li><a href="/Team:Groningen/AIModel">Read more about the AI model.
+
<section>
−
</a></li></ul></p></div>
+
<div class="split">
−
 
+
<div class="left fltwo">
−
<div class="right flone cycler">
+
<h3>Random mutations modelling</h3>
−
<img src="https://static.igem.org/mediawiki/2016/c/cc/T--Groningen---modelling---hacker-.jpeg" />
+
−
<img class="active base" src="https://static.igem.org/mediawiki/2016/b/b4/T--Groningen---modelling---MatthiaBDI-.jpeg" /></div></div>
+
 
 
 +
<p>After exploring the mutation rates in <em>B. subtilis</em>,
 +
we asked how will they affected our encrypted message and key
 +
in the genome. Therefore in this section, we computationally
 +
modelled the probability of random mutation causing our message
 +
in the DNA to be corrupted.</p>
  
−
</section>
+
<ul>
 +
<li><a href="/Team:Groningen/RandomMutation">Read more about the random mutations modelling.</a></li>
 +
</ul>
 +
</div>
  
 +
<div class="right flone cycler">
 +
<img src="https://static.igem.org/mediawiki/2016/c/c9/T--Groningen---modelling---MatthiaRandom-.jpeg " />
 +
<img class="active base" src="https://static.igem.org/mediawiki/2016/2/20/T--Groningen---modelling---whatifmutation-.jpeg" />
 +
</div>
 +
</div>
 +
</section>
  
−
<section>
 
−
<h2>Random mutations in <em>Bacillus subtilis</em> </h2>
 
−
<p>
 
  
−
<div class="split"><div class="right fltwo">We realized a random mutation would be unpleasant (see photo) in our CryptoGErM project. The data stored in the CryptoGErM system might be endangered by random mutations in the DNA. This article contains research of the literature on known mutation rates of <em>B. subtilis</em> under the special conditions and treatments that will be applied.
+
<section>
 +
<div class="split">
 +
<div class="right fltwo">
 +
<h3>Decoding fidelity</h3>
 +
 +
<p>Our sequence of the encrypted message is integrated in the  
 +
genome of <em>B. subtilis</em>, but how sure can we be that we
 +
get the same sequence back using common techniques. In the
 +
decoding fidelity section we explore how accurate the current
 +
sequencing techniques are and how strong our decoy encryption
 +
security layer is.</p>
 +
 +
<ul>
 +
<li><a href="/Team:Groningen/DecodingFidelity">Read more about decoding fidelity.</a></li>
 +
</ul>
 +
</div>
  
−
<p><ul><li><a href="/Team:Groningen/MutationRates">Read more about the <em>Bacillus subtilis</em> mutation rates.
+
<div class="left flone">
−
</a></li></ul></p></div>
+
<img src="https://static.igem.org/mediawiki/2016/e/ee/T--Groningen---modelling---decodingcosts-.png" />
 +
</div>
 +
</div>
 +
</section>
  
−
<div class="left flone"><img src="https://static.igem.org/mediawiki/2016/1/11/T--Groningen---modelling---eikemutation-.jpeg" /></div></div>
+
<section>
 +
<div class="split">
 +
<div class="left fltwo">
 +
<h3>Searching for an optimal strain</h3>
 +
 +
<p>We plan to hide our key sequence in one <em>B. subtilis</em>  
 +
strain, which is mixed with decoy <em>B. subtilis</em> spores.
 +
To select the key strain we found the photoswitchable
 +
antibiotic spirofloxacin as an interesting option. We modelled
 +
the protein-DNA interactions in order to search for an optimal
 +
strain for our photoswitchable antibiotic experiments.</p>
  
−
+
<ul>
 +
<li><a href="/Team:Groningen/SpiroModel">Read more about the spirofloxacin modelling.</a></li>
 +
</ul>
 +
</div>
  
−
</p>
+
<div class="right flone">
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</section>
+
<img src="https://static.igem.org/mediawiki/2016/6/68/T--Groningen---spiromodelling---spirogif-.gif" />
−
 
+
</div>
−
 
+
</div>
−
 
+
</section>
−
<section>
+
−
 
+
−
<h2>Random mutations modelling</h2>
+
−
<p>
+
−
 
+
−
<div class="split"><div class="left fltwo">After exploring the mutation rates in <em>B. subtilis</em>, we asked how will they affected our encrypted message and key in the genome. Therefore in this section, we computationally modelled the probability of random mutation causing our message in the DNA to be corrupted.
+
−
 
+
−
 
+
−
 
+
−
<p><ul><li><a href="/Team:Groningen/RandomMutation">Read more about the random mutations modelling.
+
−
</a></li></ul></p></div>
+
−
 
+
−
 
+
−
 
+
−
 
+
−
<div class="right flone cycler">
+
−
<img src="https://static.igem.org/mediawiki/2016/c/c9/T--Groningen---modelling---MatthiaRandom-.jpeg " />
+
−
<img class="active base" src="https://static.igem.org/mediawiki/2016/2/20/T--Groningen---modelling---whatifmutation-.jpeg" /></div></div>
+
−
 
+
−
 
+
−
 
+
−
 
+
−
</p>
+
−
</section>
+
−
 
+
−
 
+
−
<section>
+
−
<h2>Decoding fidelity</h2>
+
−
<p>
+
−
 
+
−
<div class="split"><div class="right fltwo">Our sequence of the encrypted message is integrated in the genome of <em>B. subtilis</em>, but how sure can we be that we get the same sequence back using common techniques. In the decoding fidelity section we explore how accurate the current sequencing techniques are and how strong our decoy encryption security layer is.
+
−
 
+
−
 
+
−
 
+
−
<p><ul><li><a href="/Team:Groningen/DecodingFidelity">Read more about decoding fidelity.
+
−
</a></li></ul></p></div>
+
−
 
+
−
<div class="left flone"><img src="https://static.igem.org/mediawiki/2016/e/ee/T--Groningen---modelling---decodingcosts-.png" /></div></div>
+
−
 
+
−
</p>
+
−
</section>
+
−
 
+
−
 
+
−
 
+
−
<section>
+
−
<h2>Searching for an optimal strain</h2>
+
−
<p>
+
−
 
+
−
<div class="split"><div class="left fltwo">
+
−
We plan to hide our key sequence in one <em>B. subtilis</em> strain, which is mixed with decoy <em>B. subtilis</em> spores. To select the key strain we found the photoswitchable antibiotic spirofloxacin as an interesting option. We modelled the protein-DNA interactions in order to search for an optimal strain for our photoswitchable antibiotic experiments.
+
−
 
+
−
 
+
−
<p><ul><li><a href="/Team:Groningen/SpiroModel">Read more about the spirofloxacin modelling.
+
−
</a></li></ul></p></div>
+
−
 
+
−
<div class="right flone"><img src="https://static.igem.org/mediawiki/2016/6/68/T--Groningen---spiromodelling---spirogif-.gif" /></div></div>
+
−
 
+
−
</p>
+
−
</section>
+
−
+
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+
−
+
 
</article>
 
</article>
 
</html>
 
</html>

Revision as of 16:12, 19 October 2016

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Modelling

During the CryptoGErM project we came across several problems and questions that we could not solve in the lab. Therefore we made use of several different modelling approaches. Using artificial intelligence, mathematical models and protein-DNA interaction models we could draw essential conclusions for our project.

Belief-Desire-Intention Model

We asked ourselves what happens if someone tries to hack our system (see photo). How would this person behave? Using an artificial intelligence (AI) model, we explored the behaviour of the people who use, or try to abuse, the CryptoGErM system. The people are modelled in a multi-agent simulation using genetic algorithms. This model helps us to predict the and intentions of the users and intruders of our system.

Random mutations in Bacillus subtilis

We realized a random mutation would be unpleasant (see photo) in our CryptoGErM project. The data stored in the CryptoGErM system might be endangered by random mutations in the DNA. This article contains research of the literature on known mutation rates of B. subtilis under the special conditions and treatments that will be applied.

Random mutations modelling

After exploring the mutation rates in B. subtilis, we asked how will they affected our encrypted message and key in the genome. Therefore in this section, we computationally modelled the probability of random mutation causing our message in the DNA to be corrupted.

Decoding fidelity

Our sequence of the encrypted message is integrated in the genome of B. subtilis, but how sure can we be that we get the same sequence back using common techniques. In the decoding fidelity section we explore how accurate the current sequencing techniques are and how strong our decoy encryption security layer is.

Searching for an optimal strain

We plan to hide our key sequence in one B. subtilis strain, which is mixed with decoy B. subtilis spores. To select the key strain we found the photoswitchable antibiotic spirofloxacin as an interesting option. We modelled the protein-DNA interactions in order to search for an optimal strain for our photoswitchable antibiotic experiments.


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