Difference between revisions of "Team:Valencia UPV/Model"
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The aim of the Testing System is to provide information about the gRNA ability to localize the target. Therefore, <b>external</b> and <b>intrinsic</b> factors affecting the CRISPR/Cas9 mechanism should be blocked, letting us <b>relate the light measurement exclusively with the gRNA efficacy</b> to find the target. Moreover, this system emulates the performance of the gRNA in the real variety which is desired to be improved. Thus, the fact of implementing the Testing System in <i>Nicotiana benthamiana</i> should not affect the reliability of the result, making it <b>scalable</b> and <b>realistic</b>.</p> | The aim of the Testing System is to provide information about the gRNA ability to localize the target. Therefore, <b>external</b> and <b>intrinsic</b> factors affecting the CRISPR/Cas9 mechanism should be blocked, letting us <b>relate the light measurement exclusively with the gRNA efficacy</b> to find the target. Moreover, this system emulates the performance of the gRNA in the real variety which is desired to be improved. Thus, the fact of implementing the Testing System in <i>Nicotiana benthamiana</i> should not affect the reliability of the result, making it <b>scalable</b> and <b>realistic</b>.</p> | ||
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<p>The goal is to characterize the performance of our Testing System in <i>Nicotiana benthamiana</i>, studying the influence of different factors affecting each stage of the CRIPSR/Cas9 mechanism. We have developed a mathematical model able to represent our system's performance, structured in the main steps of CRISPR/Cas9:<br><br></p> | <p>The goal is to characterize the performance of our Testing System in <i>Nicotiana benthamiana</i>, studying the influence of different factors affecting each stage of the CRIPSR/Cas9 mechanism. We have developed a mathematical model able to represent our system's performance, structured in the main steps of CRISPR/Cas9:<br><br></p> | ||
| − | <p><br> | + | <p><br><br> |
This model has been used to simulate <b>different conditions</b> that result in variations of our reporter: Luciferase. Thus, we can analyze determinant factors affecting Testing System repeatability, <b>reliability</b> and <b>robustness</b>, which are mandatory achievements in order to spread our gRNA <b>Testing System as a standard gRNA efficiency predictor</b>. | This model has been used to simulate <b>different conditions</b> that result in variations of our reporter: Luciferase. Thus, we can analyze determinant factors affecting Testing System repeatability, <b>reliability</b> and <b>robustness</b>, which are mandatory achievements in order to spread our gRNA <b>Testing System as a standard gRNA efficiency predictor</b>. | ||
<br><br><br></p></div></div> | <br><br><br></p></div></div> | ||
Revision as of 08:08, 2 December 2016
Model
Index
Overview.
The mechanism of CRISPR/Cas9 relies on binding and unbinding reactions, gene expression regulation, diffusion of biochemical compounds inside the nucleus and even thermodynamics. All these processes will affect the results obtained using the Testing System.
The aim of the Testing System is to provide information about the gRNA ability to localize the target. Therefore, external and intrinsic factors affecting the CRISPR/Cas9 mechanism should be blocked, letting us relate the light measurement exclusively with the gRNA efficacy to find the target. Moreover, this system emulates the performance of the gRNA in the real variety which is desired to be improved. Thus, the fact of implementing the Testing System in Nicotiana benthamiana should not affect the reliability of the result, making it scalable and realistic.
The goal is to characterize the performance of our Testing System in Nicotiana benthamiana, studying the influence of different factors affecting each stage of the CRIPSR/Cas9 mechanism. We have developed a mathematical model able to represent our system's performance, structured in the main steps of CRISPR/Cas9:
This model has been used to simulate different conditions that result in variations of our reporter: Luciferase. Thus, we can analyze determinant factors affecting Testing System repeatability, reliability and robustness, which are mandatory achievements in order to spread our gRNA Testing System as a standard gRNA efficiency predictor.
