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A machine learning framework predicts oncogenic driver mutations from SNP profiles in lung adenocarcinoma

Junyu Li1,2, Zuxiu Wang3, Yuchen Xia4

  • 1Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310022, Zhejiang, China.

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|March 14, 2026
PubMed
Summary

No abstract available in PubMed .

Keywords:
Driver gene mutationGradient boosting decision treeMachine learningNon-small cell lung cancer

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A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
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