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Identifying signaling genes in spatial single cell expression data.
Bioinformatics ( IF 4.4 ) Pub Date : 2020-09-04 , DOI: 10.1093/bioinformatics/btaa769
Dongshunyi Li 1 , Jun Ding 1 , Ziv Bar-Joseph 1, 2
Affiliation  

Recent technological advances enable the profiling of spatial single cell expression data. Such data presents a unique opportunity to study cell-cell interactions and the signaling genes that mediate them. However, most current methods for the analysis of this data focus on unsupervised descriptive modeling, making it hard to identify key signaling genes and quantitatively assess their impact.

中文翻译:

识别空间单细胞表达数据中的信号基因。

最近的技术进步使空间单细胞表达数据的分析成为可能。这些数据为研究细胞间相互作用和介导它们的信号基因提供了独特的机会。然而,目前大多数分析这些数据的方法都集中在无监督的描述性建模上,因此很难识别关键信号基因并定量评估它们的影响。
更新日期:2020-09-05
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