iMIRACLE:一个代的多视图图神经网络,以从空间转录基因数据模型细胞间基因调节
Ziheng Duan1, Siwei Xu1, Cheyu Lee1
1University of California, Irvine, Irvine, CA, USA.
概括
一个新的图形神经网络iMiracle通过整合基因表达和连接体-受体相互作用来解码细胞-细胞通信. 这种方法改善了空间转录学分析,以了解细胞间调节.
科学领域:
- 基因组学就是基因组学.
- 计算生物学 计算生物学
- 系统生物学 系统生物学
背景情况:
- 空间转录学使细胞微环境中的基因表达分析成为可能.
- 通过连接体-受体 (LR) 相互作用的细胞-细胞通信 (CCC) 驱动细胞反应.
- 现有的方法缺乏强大的方法来将CCC与基因表达变化联系起来,以获得生物学见解.
研究的目的:
- 开发一种用于建模细胞间调节的新型计算方法.
- 将空间转录学数据与细胞间通信网络相结合.
- 推断由LR相互作用驱动的细胞特异性基因调控得分.
主要方法:
- 开发了iMiracle,一个代的多视图图形神经网络.
- 集成的细胞间和细胞内网络用于基因表达估计.
- 采用代学习来解决CCC网络中的数据稀疏性.
- 使用LR对贡献推断的细胞特异性联体基因调控得分.
主要成果:
- iMiracle 在不同数据集的基因表达赋值中表现出卓越的性能.
- 该方法在推断监管得分方面表现优于现有的方法.
- 评估了来自三个平台的九个模拟和八个真实空间转录组数据集.
结论:
- 通过整合基因表达和CCC数据,iMiracle有效地建模细胞间调节.
- 该工具通过提供细胞特异性监管洞察力,提高了空间转录学的解释性.
- iMiracle是一款开源软件,旨在促进细胞间通信和转录调节的研究.
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