"
Team:NTNU Trondheim/Modeling
From 2011.igem.org
(Difference between revisions)
| Line 5: | Line 5: | ||
== '''Model Introduction''' == | == '''Model Introduction''' == | ||
| - | -What to model | + | -What to model |
| + | |||
-How to model | -How to model | ||
| Line 16: | Line 17: | ||
== The Models== | == The Models== | ||
| + | |||
=== Systems of ODE === | === Systems of ODE === | ||
| Line 24: | Line 26: | ||
=== Bayesian Hierarchy === | === Bayesian Hierarchy === | ||
| - | + | We den wish to model the reliability for the observations... That is the probability of false positive/negative results P(RTF = 1|stress) and opposite. | |
| + | Having the observations x_i, i = 0,1,...,n, and y_j , j = 0,1,...,m, were x_i is under condition C = 1 (stress) , and y_j is under condition C = 0 (no stress). | ||
=== Linear Classification === | === Linear Classification === | ||
Revision as of 14:56, 24 June 2011
Models are under construction -------Page
3 types of models: Systems of ODE, Bayesian hierarchy and linear classification problems (LDA or similar). To be continued....
Contents |
Model Introduction
-What to model
-How to model
The Models
Systems of ODE
Bayesian Hierarchy
We den wish to model the reliability for the observations... That is the probability of false positive/negative results P(RTF = 1|stress) and opposite. Having the observations x_i, i = 0,1,...,n, and y_j , j = 0,1,...,m, were x_i is under condition C = 1 (stress) , and y_j is under condition C = 0 (no stress).
