title: Analysis of complex traits using neural networks.
abstract: A recently developed approach that employs artificial neural networks (ANNs) was applied to the simulated data set to identify sets of marker loci involved in disease etiology. In this implementation, ANNs are trained to predict the disease state (output) from the given genetic marker data (input). A contribution value (CV) for each locus is calculated from the weights that represent the strength of the connections for the trained ANN; a higher CV indicates a higher probability of linkage. The highest CV values were chosen as the most likely candidate regions involved in the disease.
authors.affiliation: Laboratory of Statistical Genetics, Rockefeller University, New York, New York, USA.
authors.forename: A
authors.initials: A
authors.lastname: Bhat
authors.forename: P R
authors.initials: PR
authors.lastname: Lucek
authors.forename: J
authors.initials: J
authors.lastname: Ott
mesh_terms: D003198:Computer Simulation; D004777:Environment; D005820:Genetic Testing; D016678:Genome; D006801:Humans; D008957:Models, Genetic; D016571:Neural Networks, Computer; D010641:Phenotype; D012984:Software