ArticleMolecular biology reports2013
Particle swarm optimization algorithm for analyzing SNP-SNP interaction of renin-angiotensin system genes against hypertension.
Article in Molecular biology reports, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed.
- Genome-wide association and MaODR-based multi-locus interaction analyses reveal a susceptibility gene network for newly identified metabolic syndrome.Genome biology · 2026Article
- AI-enhanced integration of genetic and medical imaging data for risk assessment of Type 2 diabetes.Nature communications · 2024Article
- Cancer Detection and Prediction Using Genetic Algorithms.Computational intelligence and neuroscience · 2022Article
- Identification of High-Order Single-Nucleotide Polymorphism Barcodes in Breast Cancer Using a Hybrid Taguchi-Genetic Algorithm: Case-Control Study.JMIR medical informatics · 2020Article
- Article
- Detecting Susceptibility to Breast Cancer with SNP-SNP Interaction Using BPSOHS and Emotional Neural Networks.BioMed research international · 2016Article
- The Combinational Polymorphisms of ORAI1 Gene Are Associated with Preventive Models of Breast Cancer in the Taiwanese.BioMed research international · 2015Article
- An Improved Opposition-Based Learning Particle Swarm Optimization for the Detection of SNP-SNP Interactions.BioMed research international · 2015Article
- High order gene-gene interactions in eight single nucleotide polymorphisms of renin-angiotensin system genes for hypertension association study.BioMed research international · 2015Article
- Identification of sequence polymorphisms in the mitochondrial displacement loop as risk factors for sporadic and familial breast cancer.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2014Article
- Identification of SNP barcode biomarkers for genes associated with facial emotion perception using particle swarm optimization algorithm.Annals of general psychiatry · 2014Article
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7 authors.
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Abstract
Most non-significant individual single nucleotide polymorphisms (SNPs) were undiscovered in hypertension association studies. Their possible SNP-SNP interactions were usually ignored and leaded to missing heritability. In present study, we proposed a particle swarm optimization (PSO) algorithm to analyze the SNP-SNP interaction associated with hypertension. Genotype dataset of eight SNPs of renin-angiotensin system genes for 130 non-hypertension and 313 hypertension subjects were included. Without SNP-SNP interaction, most individual SNPs were non-significant difference between the hypertension and non-hypertension groups. For SNP-SNP interaction, PSO can select the SNP combinations involving different SNP numbers, namely the best SNP barcodes, to show the maximum frequency difference between non-hypertension and hypertension groups. After computation, the best PSO-generated SNP barcodes were dominant in non-hypertension in terms of the occurrences of frequency differences between non-hypertension and hypertension groups. The OR values of the best SNP barcodes involving 2-8 SNPs were 0.705-0.334, suggesting that these SNP barcodes were protective against hypertension. In conclusion, this study demonstrated that non-significant SNPs may generate the joint effect in association study. Our proposed PSO algorithm is effective to identify the best protective SNP barcodes against hypertension.
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