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 better classification scores and found more rules from the data generated artificially. It also obtained similar results when using some UCI Machine Learning datasets. In this chapter it is assumed that several groups of Single Nucleotide Polymorphisms (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.
|Original language||English (US)|
|Title of host publication||Soft Computing Methods for Practical Environment Solutions|
|Subtitle of host publication||Techniques and Studies|
|Number of pages||21|
|State||Published - 2010|
ASJC Scopus subject areas
- Computer Science(all)