SEEI:,.

De-Yu Tang1,2, Yi-Jun Mao3, Jie Zhao4

  • 1Department of Computer Science, School of Mathematics and Informatics, School of Software Engineering, South China Agricultural University, Guangzhou, 510642, PR China. scutdy@126.com.

BMC genomics
|May 12, 2024
PubMed
概括

检测表皮性相互作用 (EIs) 对于理解复杂疾病至关重要. 一种新的线性混合统计表征模型 (LMSE) 和球体进化方法 (SEEI) 有效地识别了EIs,优于模拟和乳腺癌数据集分析中的现有方法.

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