Machine learning techniques for single nucleotide polymorphism--disease classification models in schizophrenia.

ABSTRACT: Single nucleotide polymorphisms (SNPs) can be used as inputs in disease computational studies such as pattern searching and classification models. Schizophrenia is an example of a complex disease with an important social impact. The multiple causes of this disease create the need of new genetic or proteomic patterns that can diagnose patients using biological information. This work presents a computational study of disease machine learning classification models using only single nucleotide polymorphisms at the HTR2A and DRD3 genes from Galician (Northwest Spain) schizophrenic patients. These classification models establish for the first time, to the best knowledge of the authors, a relationship between the sequence of the nucleic acid molecule and schizophrenia (Quantitative Genotype-Disea

SUBMITTER: Aguiar-Pulido V 

PROVIDER: S-EPMC6257637 | biostudies-literature | 2010 Jul

REPOSITORIES: biostudies-literature