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<table border="1"> | <table border="1"> | ||
<tr> | <tr> | ||
− | <td> | + | <td>Parameters</td> |
<td>Meaning</td> | <td>Meaning</td> | ||
</tr> | </tr> | ||
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</tr> | </tr> | ||
<tr> | <tr> | ||
− | <td></td> | + | <tr> |
− | <td></td> | + | <td>η</td> |
+ | <td>RNAi efficiency</td> | ||
+ | </tr> | ||
+ | <tr> | ||
+ | <td>α (alpha)</td> | ||
+ | <td>GC content</td> | ||
+ | </tr> | ||
+ | <tr> | ||
+ | <td>β (beta)</td> | ||
+ | <td>Mortality. Mathematically it's the derivative of D.</td> | ||
</tr> | </tr> | ||
</table> | </table> |
Revision as of 17:50, 5 October 2018
Abstract
Our model is formalized by the Differential Equation: (Logistic Regression)
We've chosen this model as it's often used for modeling the growth and decay of a population. In our condition where we apply our pesticide to the pests, we investigate the underlying factors that affect the relationship between time and the number of deaths.
Assumptions
Parameters
Parameters | Meaning |
D(t) | Number of deaths |
η | RNAi efficiency |
α (alpha) | GC content |
β (beta) | Mortality. Mathematically it's the derivative of D. |
Experiments
Results