Difference between revisions of "Team:USP-Brazil/Modelling"

 
Line 32: Line 32:
 
             <p>A natural way to adress this issue is to model the system. As a simplification of the world, modelling biological systems allows us to look only through the most interesting aspects we want to understand. So, with that in mind, we decided to construct a model where we can answer the core-question: How much interaction is there between the system complexes and their promoters?
 
             <p>A natural way to adress this issue is to model the system. As a simplification of the world, modelling biological systems allows us to look only through the most interesting aspects we want to understand. So, with that in mind, we decided to construct a model where we can answer the core-question: How much interaction is there between the system complexes and their promoters?
 
             </p>
 
             </p>
−
             <p>With this objective in mind and, using our design as foundation, with the goal to escalate to more complex ideas, our model aimed (and achieved) three basic objectives:
+
             <p>With this objective in mind and, using our design as foundation, with the goal to escalate to more complex ideas, our model aimed (and achieved) two basic objectives:
 
             </p>
 
             </p>
 
             <ul>
 
             <ul>
 
               <li>Create a general model of quorum sensing systems, with which we can estimate the crosstalk between the systems and, therefore, be able to predict the behavior in future system studies (<a href="https://2018.igem.org/Team:USP-Brazil/Model">Single System Model and Predictions</a>)</li>
 
               <li>Create a general model of quorum sensing systems, with which we can estimate the crosstalk between the systems and, therefore, be able to predict the behavior in future system studies (<a href="https://2018.igem.org/Team:USP-Brazil/Model">Single System Model and Predictions</a>)</li>
 
               <li>Escalate the model to predict the behaviour in more complex combinations, from 2 to N systems in a single system, being able to determine the systems combinations with maximum orthogonality (<a href="https://2018.igem.org/Team:USP-Brazil/MultiModel">Multi-System Model</a>)</li>
 
               <li>Escalate the model to predict the behaviour in more complex combinations, from 2 to N systems in a single system, being able to determine the systems combinations with maximum orthogonality (<a href="https://2018.igem.org/Team:USP-Brazil/MultiModel">Multi-System Model</a>)</li>
−
              <li>Be able to use the base model to forecast applications, using the results from our studies (<a href="https://2018.igem.org/Team:USP-Brazil/ModelApplications">Application Models</a>)</li>
 
 
             </ul>
 
             </ul>
 
             <p>We also proposed some <a href="https://2018.igem.org/Team:USP-Brazil/Statistics">stochastic and statistical analysis</a>, using some mathematical and computational approaches.
 
             <p>We also proposed some <a href="https://2018.igem.org/Team:USP-Brazil/Statistics">stochastic and statistical analysis</a>, using some mathematical and computational approaches.

Latest revision as of 02:54, 18 October 2018

Wiki - iGEM Brazil

Wiki - iGEM Brazil

Model

With our project, we aimed to find a quantitative value for the crosstalk between quorum sensing systems. However, there is an intrinsic question about it: How to do it? How to look at the results of our measurements and find a relation between the systems?

A natural way to adress this issue is to model the system. As a simplification of the world, modelling biological systems allows us to look only through the most interesting aspects we want to understand. So, with that in mind, we decided to construct a model where we can answer the core-question: How much interaction is there between the system complexes and their promoters?

With this objective in mind and, using our design as foundation, with the goal to escalate to more complex ideas, our model aimed (and achieved) two basic objectives:

  • Create a general model of quorum sensing systems, with which we can estimate the crosstalk between the systems and, therefore, be able to predict the behavior in future system studies (Single System Model and Predictions)
  • Escalate the model to predict the behaviour in more complex combinations, from 2 to N systems in a single system, being able to determine the systems combinations with maximum orthogonality (Multi-System Model)

We also proposed some stochastic and statistical analysis, using some mathematical and computational approaches.