Papers

@conference{Miguélez2008304,

title = {Hybrid system for data classification of DNA microarrays with GA and SVM},

author = {Mónica Miguélez and Juan Luis Pérez-Ordóñez and Juan R. Rabuñal-Dopico and Julián Dorado},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-58049171968&partnerID=40&md5=c5cf435c8bc1f17077f828ab72bb88e8},

isbn = {9789898111524; 9789898111531},

year  = {2008},

date = {2008-01-01},

urldate = {2008-01-01},

journal = {ICSOFT 2008 - Proceedings of the 3rd International Conference on Software and Data Technologies},

volume = {ISDM},

number = {ABF/-},

pages = {304-307},

abstract = {This paper proposes a Genetic Algorithm (GA) combined with Support Vector Machine (SVM) for selecting and classifying data from DNA microarrays, with the aim of differentiate healthy from cancerous tissue samples. The proposed GA, by using a SVM fitness function, enables the selection of a group of genes that represent the absence or the presence of cancerous tissue. The proposed method is tested with a group data related to a widely known cancer disease, the breast cancer. The comparison shows that the results obtained with these combined techniques arc better than other techniques,.},

note = {cited By 0},

keywords = {Bioassay; Biochips; Computer software; DNA; Function evaluation; Genes; Hybrid systems; Support vector machines, Breast Cancer; Cancer disease; Cancerous tissues; Combined techniques; Data classification; DNA micro-array; Fitness functions; Support Vector Machine (SVM), Genetic algorithms},

pubstate = {published},

tppubtype = {conference}

}