细胞Msg:图形卷积网络用于联体受体介导的细胞-细胞通信分析
Hong Xia1, Boya Ji1, Debin Qiao2
1College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China.
Briefings in bioinformatics
|January 12, 2025
概括
CellMsg是一种新的计算工具,可以识别连接体-受体相互作用 (LRIs),并从单细胞RNA测序数据测量细胞-细胞通信 (CCC) 强度,为研究瘤组织提供了强大的方法.
科学领域:
- 计算生物学是一种计算生物学.
- 基因组学就是基因组学.
- 癌症研究 癌症研究
背景情况:
- 细胞-细胞通信 (CCCs) 在瘤组织中至关重要,影响分化,入侵,转移和耐药性.
- 对于大型数据集来说,推断CCC的传统实验方法是低效的.
研究的目的:
- 开发一个计算框架,CellMsg,用于有效推断CCCs.
- 为了确定高可信度联体受体相互作用 (LRIs) 和量化CCC强度.
主要方法:
- CellMsg使用多式联络功能和图形卷积网络来识别LRI.
- 它采用三点估计方法,将LRIs和单细胞RNA-seq数据结合起来,以测量CCC强度.
- 使用基准LRI数据集,交叉验证和分子对接来验证性能.
主要成果:
- 与现有方法相比,CellMsg准确地识别了高可信度LRIs,其预测性能和稳定性优于现有的方法.
- 识别的LRI通过分子对接来验证.
- 对人类黑色素瘤组织的分析揭示了七种细胞类型之间的细胞间交叉声.
结论:
- CellMsg提供了一个可靠的LRI数据库和一个有效的CCC强度评估方法,用于单细胞RNA-seq数据.
- 这种计算工具有助于解读生物系统中细胞间通信.
- CellMsg是公开可用于研究的.
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