Prediction of Type II MODY3 diabetes using backpercolation.

Khan, Nawaz, Chukwuemeka, Ikejiaku and Rahman, Shahedur ORCID: https://orcid.org/0000-0002-6568-6264 (2005) Prediction of Type II MODY3 diabetes using backpercolation. In: 18th IEEE Cmputer Based Medical System Conference, Dublin. Proceedings. IEEE Computer Society Press., London, pp. 401-403. ISBN 0-7695-2355-2. [Book Section] (doi:10.1109/CBMS.2005.85)

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Abstract

This paper examined the use of the backpercolation neural network algorithm to identify mutated MODY3 gene sequence data that is responsible for type II (maturity onset) diabetes. It was then demonstrated that a supervised feed forward method gave more accurate results in predicting point mutation in genes than the neural network backpropagation method. This paper brought the technique to the attention of other researchers as to how the method can be used for this and for the prediction of other diseases. The technique had been widely used in analysing environmental data is now commonly used in Bioinformatics.

Item Type: Book Section
Research Areas: A. > School of Science and Technology > Computer Science
A. > School of Science and Technology > Computer and Communications Engineering
Item ID: 93
Useful Links:
Depositing User: Repository team
Date Deposited: 21 Oct 2008 11:06
Last Modified: 23 Jun 2021 12:47
URI: https://eprints.mdx.ac.uk/id/eprint/93

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