莫拉和EnsembleTFpredictor:一个集体方法来揭示功能转录因子监管网络
Kevin Boyer1, Louis Li2, Tiandao Li3
1Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, United States of America.
PloS one
|November 30, 2023
概括
我们开发了动机对表现分析 (MORA) 和EnsembleTF预测器工具,以识别控制基因表达的转录因子. 这些计算方法增强了基因调节研究的生物发现和实验设计.
科学领域:
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 识别转录因子 (TFs) 对于理解基因表达调节至关重要.
- 共同表达或共同调节的基因往往具有共同的调节元素,由特定的TFs控制.
研究的目的:
- 开发和验证用于识别生物相关转录因子的计算工具.
- 在基因序列中检测已知TF结合基因的丰富.
- 提供具有预测可靠性的功能TF的排名列表.
主要方法:
- 开发一个完全自动化的管道,动机过度表示分析 (MORA),用于TF绑定动机丰富分析.
- 创建了EnsembleTFpredictor,这是一个整合多种TF预测方法的工具.
- 使用基因表达和ChIP-seq数据集对其他五种TF预测工具进行MORA的评估.
主要成果:
- 摩拉的性能与现有的TF预测工具相提并论或优于它们.
- EnsembleTFpredictor在生物系统中成功识别了目标TF和合作TF.
- 在已发表的研究中,MORA和EnsembleTFpredictor都已成功应用.
结论:
- MORA和EnsembleTFpredictor是识别调节基因表达的转录因子的强大工具.
- 这些工具可以指导实验设计,并揭示对基因调节的新生物学见解.
- 开发的方法为TF预测和图案丰富分析提供了强大的解决方案.
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