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Identify specific gene pairs for subarachnoid hemorrhage based on wavelet analysis and genetic algorithm

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  • Pengcheng Zhao
  • Shaonian Xu
  • Zhenshan Huang
  • Pengcheng Deng
  • Yongming Zhang

Abstract

Subarachnoid hemorrhage (SAH) is a fatal stroke caused by bleeding in the brain. SAH can be caused by a ruptured aneurysm or head injury. One-third of patients will survive and recover. One-third will survive with disability; one-third will die. The focus of treatment is to stop bleeding, restore normal blood flow, and prevent vasospasm. Treatment for SAH varies, depending on the bleeding’s underlying cause and the extent of damage to the brain. Treatment may include lifesaving measures, symptom relief, repair of the bleeding vessel, and complication prevention. However, the useful diagnostic biomarkers of SAH are still limited due to the instability of gene marker expression. To overcome this limitation, we developed a new protocol pairing genes and screened significant gene pairs based on the feature selection algorithm. A classifier was constructed with the selected gene pairs and achieved a high performance.

Suggested Citation

  • Pengcheng Zhao & Shaonian Xu & Zhenshan Huang & Pengcheng Deng & Yongming Zhang, 2021. "Identify specific gene pairs for subarachnoid hemorrhage based on wavelet analysis and genetic algorithm," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-20, June.
    • Handle: RePEc:plo:pone00:0253219
    DOI: 10.1371/journal.pone.0253219
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    1. Patrick K. Kimes & Yufeng Liu & David Neil Hayes & James Stephen Marron, 2017. "Statistical significance for hierarchical clustering," Biometrics, The International Biometric Society, vol. 73(3), pages 811-821, September.
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