自网络:用于分析自及其调节的高分辨率数据源
Luca Csabai1,2, Balázs Bohár1,2, Dénes Türei3
1Earlham Institute, Norwich, UK.
Autophagy
|August 17, 2023
概括
自网络是自研究的升级数据库,整合了超过28万个相互作用,以了解健康和疾病中的自调节. 该资源有助于分析复杂的自网络及其在各种条件下的作用.
科学领域:
- 细胞生物学 细胞生物学
- 分子生物学分子生物学
- 系统生物学 系统生物学
背景情况:
- 宏自/自是一个关键的细胞过程,用于去除受损的组件和病原体.
- 功能失调的自与癌症,神经退行和炎症等疾病有关.
- 了解自调节对于基础研究和治疗开发都至关重要.
研究的目的:
- 介绍AutophagyNet,一个增强和更新的自研究数据库.
- 为探索自监管网络提供一个全面的资源.
- 促进对健康和疾病中自的多层调节的研究.
主要方法:
- 策划和整合了超过28万个经过实验验证的交互.
- 包含了关于蛋白质,转录和转录后调节器的数据.
- 增加了核心自蛋白的注释,说明它们的作用,阶段和定位.
主要成果:
- AutophagyNet提供最新的交互数据和新的omics集成功能.
- 数据库包括详细的注释,用于可定制的数据过和下载.
- 该资源支持通过CSV,BioPAX,PSI-MI和Cytoscape等格式进行分析和可视化.
结论:
- 自网络是自研究社区的一个有价值的,公开可访问的资源.
- 它通过整合各种数据集,使得对自调节的深入分析成为可能.
- 该平台支持对自在各种生物过程和疾病中的作用的调查.
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