Gene regulatory network inference in single-cell biology
Gene regulatory network inference in single-cell biology
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DOI：
10.1016/j.coisb.2021.04.007
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发表时间：
2021-06-01
影响因子：
3.7
通讯作者：
Murali, T. M.
中科院分区：
文献类型：
--
作者：
Akers, Kyle;Murali, T. M.
基因调控网络记录转录因子与它们控制表达的基因之间的关系。最近的计算方法已经发展到预测这些调控相互作用的基础上产生的基因表达数据的单细胞测序技术。在这篇综述中，我们总结了这些基因调控网络推理算法，用于评估预测的调控相互作用的方法，以及模拟scRNA-seq数据的方法。最后，我们讨论了单细胞多组学的发展趋势，我们希望影响未来的研究网络推理。
Gene regulatory networks record relationships between transcription factors and the genes whose expression they control. Recent computational methods have been developed to predict these regulatory interactions based on gene expression data generated by single-cell sequencing technologies. In this review, we summarize these gene regulatory network inference algorithms, methods for evaluating predicted regulatory interactions, and approaches to simulate scRNA-seq data. We conclude by discussing developing trends in single-cell multiomics that we expect to influence future research on network inference.