Difference between revisions of "Team:Vilnius-Lithuania-OG/Model"

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<title>Collaborations</title>
  
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<h1> Modeling</h1>
 
  
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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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<h3> Gold Medal Criterion #3</h3>
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Convince the judges that your project's design and/or implementation is based on insight you have gained from modeling. This could be either a new model you develop or the implementation of a model from a previous team. You must thoroughly document your model's contribution to your project on your team's wiki, including assumptions, relevant data, model results, and a clear explanation of your model that anyone can understand.
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The model should impact your project design in a meaningful way. Modeling may include, but is not limited to, deterministic, exploratory, molecular dynamic, and stochastic models. Teams may also explore the physical modeling of a single component within a system or utilize mathematical modeling for predicting function of a more complex device.
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Please see the <a href="https://2018.igem.org/Judging/Medals"> 2018
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<h3>Best Model Special Prize</h3>
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To compete for the <a href="https://2018.igem.org/Judging/Awards">Best Model prize</a>, please describe your work on this page  and also fill out the description on the <a href="https://2018.igem.org/Judging/Judging_Form">judging form</a>. Please note you can compete for both the gold medal criterion #3 and the best model prize with this page.
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You must also delete the message box on the top of this page to be eligible for the Best Model Prize.
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<h2 data-caption-animate="fadeInUp">MODELS</h2>
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data-href="#section-droplet">Droplet coalescence</a></li>
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<li><a href="#" data-href="#section-mutant">In-silico mutant determination</a></li>
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<li><a href="#" data-href="#section-inhibitory">Modified nucleotide inhibitory effect</a></li>
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<p>During the development of CAT-Seq we have developed three different in-depth mathematical models that have immensely helped us create a well-working system.</p>
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<h2>Mathematical description of droplet coalescence</h2>
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<p>Efficient reaction mix enrichment by droplet merging was an extremely important aspect of CAT-Seq as it is directly responsible for the accuracy and information retainment degree. Yet, the droplet merging was immensely inefficient, as droplet coalescence techniques contain multiple parameters that requires precise tuning. For that reason we have developed an in-depth mathematical description of the droplet merging. Explore the model by <span><a href="https://2018.igem.org/Team:Vilnius-Lithuania-OG/Merging_Model"> clicking here</a></span>.</p>
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<h2>In-silico determination of Esterase mutants</h2>
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<p>In order to assess the CAT-Seq accuracy and precision, using in-silico methods we have derived CAT-Seq esterase mutants which had different activities, which would be later used for Catalytic Activity Sequencing performance benchmarking. Explore the model by <span><a href="https://2018.igem.org/Team:Vilnius-Lithuania-OG/MutationModel"> clicking here</a></span>.</p>
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<h2>Modified Nucleotide inhibitory effect model</h2>
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<p>While researching the literature we have found out that modified nucleotides (which we are using as substrate nucleotides) might sometimes affect the amplification efficiency of Phi29 polymerase. We were concerned by that fact because the amplification efficiency was important for us, as nanopore sequence requires long amplicons. For this reason we have derived a mathematical model to assess the modified nucleotide inhibitory effects on the DNA amplicon length. <span><a href="https://2018.igem.org/Team:Vilnius-Lithuania-OG/Inhibitory_Model"> clicking here</a></span>.</p>
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<h3> Inspiration </h3>
 
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Here are a few examples from previous teams:
 
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<li><a href="https://2016.igem.org/Team:Manchester/Model">2016 Manchester</a></li>
 
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<li><a href="https://2016.igem.org/Team:TU_Delft/Model">2016 TU Delft</li>
 
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<li><a href="https://2014.igem.org/Team:ETH_Zurich/modeling/overview">2014 ETH Zurich</a></li>
 
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<li><a href="https://2014.igem.org/Team:Waterloo/Math_Book">2014 Waterloo</a></li>
 
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Revision as of 21:13, 17 October 2018

Collaborations

MODELS

Explore MODELS

During the development of CAT-Seq we have developed three different in-depth mathematical models that have immensely helped us create a well-working system.

Mathematical description of droplet coalescence

Efficient reaction mix enrichment by droplet merging was an extremely important aspect of CAT-Seq as it is directly responsible for the accuracy and information retainment degree. Yet, the droplet merging was immensely inefficient, as droplet coalescence techniques contain multiple parameters that requires precise tuning. For that reason we have developed an in-depth mathematical description of the droplet merging. Explore the model by clicking here.

In-silico determination of Esterase mutants

In order to assess the CAT-Seq accuracy and precision, using in-silico methods we have derived CAT-Seq esterase mutants which had different activities, which would be later used for Catalytic Activity Sequencing performance benchmarking. Explore the model by clicking here.

Modified Nucleotide inhibitory effect model

While researching the literature we have found out that modified nucleotides (which we are using as substrate nucleotides) might sometimes affect the amplification efficiency of Phi29 polymerase. We were concerned by that fact because the amplification efficiency was important for us, as nanopore sequence requires long amplicons. For this reason we have derived a mathematical model to assess the modified nucleotide inhibitory effects on the DNA amplicon length. clicking here.