基准测试DNA结合亲缘关系模型使用异位基因特异性转录因子结合数据
Xiaoting Li1, Lucas A N Melo1, Harmen J Bussemaker1,2
1Department of Biological Sciences, Columbia University, New York, NY 10027, USA.
bioRxiv : the preprint server for biology
|January 3, 2024
概括
本研究引入了一个新的框架,用于使用ChIP-seq数据对转录因子 (TF) 结合模型进行基准测试. 这种方法增强了对等位基特异性结合 (ASB) 的检测,并使新的动机发现成为可能.
科学领域:
- 基因组学和分子生物学
- 生物信息学和计算生物学
背景情况:
- 转录因子 (TFs) 呈现出序列特异性的DNA结合,这可能导致异构位的等位基特异性结合 (ASB).
- 标准的ChIP-seq测定通常缺乏在整个基因组的个体变异水平上检测ASB的统计能力.
- 准确的TF结合模型对于理解基因调节及其变异至关重要.
结论:
- 开发的框架提供了一个可靠的方法,用于对TF结合模型进行基准测试,并增强对等位基因特定结合的检测.
- PyProBound实现提供了改进的TF绑定预测,因为它考虑了特定序列的偏差.
- 概率函数可以有效地用于直接从原始等位基因意识的ChIP-seq计数中进行de novo动机发现.
关键词:
在CTCF中,CTCF是指CTCF.在 ChIP-seqq.具有DNA结合的特异性基因表达调节 基因表达调节一个等位基因特定的结合.机器学习是生物物理解释的机器学习.发现动机 发现动机没有编码的遗传变异.统计建模 统计建模转录因子是一种转录因子.更多相关视频
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