DocumentCode :
3390984
Title :
Classifier ensemble based analysis of a genome-wide SNP dataset concerning Late-Onset Alzheimer Disease
Author :
Coelho, Lúcio ; Goertzel, Ben ; Pennachin, Cassio ; Heward, Chris
Author_Institution :
Biomind LLC, Rockville, MD, USA
fYear :
2009
fDate :
15-17 June 2009
Firstpage :
469
Lastpage :
475
Abstract :
The OpenBiomind toolkit is used to apply GA, GP and local search methods to analyze a large SNP dataset concerning late-onset Alzheimer´s disease (LOAD). Classification models identifying LOAD with statistically significant accuracy are identified, and ensemble-based important features analysis is used to identify brain genes related to LOAD, most notably the solute carrier gene SLC6A15. Ensemble analysis is used to identify potentially significant interactions between genes in the context of LOAD.
Keywords :
brain; diseases; genetic algorithms; genetic engineering; learning (artificial intelligence); medical administrative data processing; search problems; OpenBiomind toolkit; SLC6A15; brain genes; classifier ensemble based analysis; genetic algorithms; genetic programming; genome-wide SNP dataset; important features analysis; late-onset Alzheimer disease; local search methods; single-nucleotide polymorphisms; Algorithm design and analysis; Alzheimer´s disease; Bioinformatics; Biological information theory; Data analysis; Genetic programming; Genomics; Machine learning; Search methods; Testing; Alzheimer; GA; GP; SNP;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cognitive Informatics, 2009. ICCI '09. 8th IEEE International Conference on
Conference_Location :
Kowloon, Hong Kong
Print_ISBN :
978-1-4244-4642-1
Type :
conf
DOI :
10.1109/COGINF.2009.5250695
Filename :
5250695
Link To Document :
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