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Team:Prairie View/Modeling
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Revision as of 21:45, 29 October 2008
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Contents |
Artifical Neural Network Modeling of the Molecular Biosensor
Training using back propagation
:Select function in matlab library to fit data
Find error, and compare to target error
General error function
Finally select function that gives least error
Sigmoid function
An enose is an analytic device originally used for detecting chemicals and their concentrations in vapors
Using E-Nose allow us to apply it to a metal sensor by finding the functional relationship, which is the response to the concentration and type of metal
Now that we have built our Molecular Sensor , with E-Nose we can:
Use experimental data for individual metal ion protein sequence, and ligations
Look at a wider range of variation in the concentrations
Collect data from rejected samples to determine the reliability of network
And use the completion of the final network to identify the ion as well as it’s corresponding concentration
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