Name
Abstract | ||
|---|---|---|
A new algorithm is presented for finding genotype-phenotype association rules from data related to complex diseases. The algorithm was based on Genetic Algorithms, a technique of Evolutionary Computation. The algorithm was compared to several traditional data mining techniques and it was proved that it obtained similar classification scores but found more rules from the data generated artificially. In this paper it is assumed that several groups of SNPs have an impact on the predisposition to develop a complex disease like schizophrenia. It is expected to validate this in a short period of time on real data. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-02478-8_115 | IWANN (1) |
Keywords | Field | DocType |
genetic algorithms,complex disease,short period,genotype-phenotype association rule,data mining,complex diseases,evolutionary computation,similar classification score,new algorithm,traditional data mining technique,association rule,evolutionary computing,association studies,snps,genetic algorithm | Interactive evolutionary computation,Data mining,Computer science,Evolutionary computation,FSA-Red Algorithm,Association rule learning,Genetic representation,Artificial intelligence,Genetic algorithm,Machine learning | Conference |
Volume | ISSN | Citations |
5517 | 0302-9743 | 3 |
PageRank | References | Authors |
0.39 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vanessa Aguiar-Pulido | 1 | 10 | 3.28 |
| José A. Seoane | 2 | 76 | 9.29 |
| Ana Freire | 3 | 35 | 4.16 |
| Cristian R. Munteanu | 4 | 100 | 10.27 |