期刊
MOLECULES
卷 15, 期 7, 页码 4875-4889出版社
MDPI
DOI: 10.3390/molecules15074875
关键词
DNA molecule; SNP; schizophrenia; artificial neural networks; evolutionary computation
资金
- General Directorate of Quality and Management of Galicia's University System of the Xunta
- Xunta de Galicia (Spain)
- General Directorate of Scientific and Technologic Promotion of the Galician University System of Xunta de Galicia [2009/58]
- CYTED [209RT0366]
- COMBIOMED [PIO52048, RD07/0067/0005]
- Carlos III Health Institute
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-Disease Relationships) that can automatically recognize schizophrenia DNA sequences and correctly classify between 78.3-93.8% of schizophrenia subjects when using datasets which include simulated negative subjects and a linear artificial neural network.
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