Tong, D. L., Phalp, K. T., Schierz, A. C. and Mintram, R., 2009. Innovative Hybridisation of Genetic Algorithms and Neural Networks in Detecting Marker Genes for Leukaemia Cancer. In: 4th IAPR International Conference in Pattern Recognition for Bioinformatics, 7-9 September 2009, Sheffield, UK.
This is the latest version of this eprint.
Full text available as:
Methods for extracting marker genes that trigger the growth of cancerous cells from a high level of complexity microarrays are of much interest from the computing community. Through the identified genes, the pathology of cancerous cells can be revealed and early precaution can be taken to prevent further proliferation of cancerous cells. In this paper, we propose an innovative hybridised gene identification framework based on genetic algorithms and neural networks to identify marker genes for leukaemia disease. Our approach confirms that high classification accuracy does not ensure the optimal set of genes have been identified and our model delivers a more promising set of genes even with a lower classification accuracy
|Item Type:||Conference or Workshop Item (Paper)|
|Additional Information:||2009 Electronic Publication|
|Subjects:||Generalities > Computer Science and Informatics > Artificial Intelligence|
Science > Biology and Botany
|Group:||Faculty of Science and Technology|
|Deposited By:||Dr Amanda C. Schierz LEFT|
|Deposited On:||21 Mar 2010 19:36|
|Last Modified:||10 Sep 2014 14:48|
Available Versions of this Item
Downloads per month over past year
|Repository Staff Only -|