MBC PathNet:集成和可视化连接功能相关路径的网络,这些路径是从转录组和蛋白组数据集中预测的
Jens Hansen1,2, Ravi Iyengar1,2
1Mount Sinai Institute for Systems Biomedicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States.
Bioinformatics advances
|September 8, 2025
概括
细胞通路网络的分子生物学 (PathNet) 集成和可视化来自基因和蛋白质列表的通路数据. 该工具有助于在多个数据集中探索共享和独特的生物机制.
科学领域:
- 分子生物学分子生物学
- 生物信息学是一种生物信息学.
- 系统生物学 系统生物学
背景情况:
- 高通量技术使单细胞和空间转录组/蛋白组分析成为可能.
- 基因/蛋白质数据的增加需要先进的途径-网络集成策略.
- 探索跨数据集的共享和独特的生物机制至关重要.
研究的目的:
- 介绍细胞的分子生物学 (MBC) 路径网络 (PathNet) 以集成和可视化路径数据.
- 为了方便快速探索路径之间的功能关系.
- 为分析复杂的生物数据集提供一个工具.
主要方法:
- MBC PathNet集成了来自基因和蛋白质列表的途径信息.
- 利用细胞本体学的分子生物学和其他本体学.
- 可视化路径作为交互网络与代表数据集的饼图.
主要成果:
- 路径网络使功能相关的路径可视化.
- 圆形图表表示数据集贡献,大小表示定量措施.
- 支持层次和功能路径关系.
- 生成条形图,热图和时间线.
- 提供完全自动化的命令行执行.
结论:
- MBC PathNet提供了一种有效的途径网络集成和可视化方法.
- 方便在各种数据集中探索复杂的生物机制.
- 支持对大型生物数据进行自动化分析.
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