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Article

Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests.

BMC genomics - 1 Jan 2015

Nguyen Thanh-Tung, Huang Joshua, Wu Qingyao, Nguyen Thuy, Li Mark

Abstract excerpt

BACKGROUND: Single-nucleotide polymorphisms (SNPs) selection and identification are the most important tasks in Genome-wide association data analysis. The problem is difficult because genome-wide association data is very high dimensional and a large portion of SNPs in the data is irrelevant to the disease. Advanced machine learning methods have been successfully used in Genome-wide association studies (GWAS) for...

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PMID: 25708662
DOI: 10.1186/1471-2164-16-S2-S5
PMCID: PMC4331719

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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