通过深度学习模型预测人类基因组中的Alu外化.
Zitong He1, Ou Chen2, Noelani Phillips3
1Department of Computer Science, Johns Hopkins University, Baltimore, MD 21205.
bioRxiv : the preprint server for biology
|January 23, 2024
概括
异化,即将元素整合到基因中,比以前认为的更为普遍. 我们的深度学习模型eXAlu识别了许多新的Alu外电化事件,进步了我们对基因调节的理解.
科学领域:
- 基因组学就是基因组学.
- 分子生物学分子生物学
- 生物信息学是一种生物信息学.
背景情况:
- 外化有助于功能基因多样化,但其全部范围和监管影响尚不清楚.
- 目前用于识别Alu外化的现有方法受到组织特异性和计算需求的限制.
结论:
- 外化是一个比以前估计的更重要的基因组现象.
- eXAlu提供了一个强大的,计算效率高的工具,用于发现Alu外电化事件.
- 这种方法对理解基因调节和人类遗传变异有影响.
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