在心血管蛋白质组学中发现蛋白质网络
Maria Hasman1, Manuel Mayr1, Konstantinos Theofilatos1
1King's British Heart Foundation Centre, Kings College London, London, United Kingdom.
Molecular & cellular proteomics : MCP
|June 25, 2023
概括
本综述探讨了构建和分析生物网络的计算方法,重点关注它们在心血管疾病中的应用. 它强调使用单细胞RNA测序用于生物标志物发现和药物向的组织特异性网络重建和解释.
科学领域:
- 生物信息学是一种生物信息学.
- 系统生物学 系统生物学
- 计算生物学 计算生物学
背景情况:
- 生物网络对于识别疾病生物标志物和药物点至关重要.
- 蛋白质网络分析已经应用于各种疾病.
- 心血管疾病是基于网络的研究的一个重要领域.
研究的目的:
- 审查用于重建和分析蛋白质网络的计算技术.
- 总结这些技术在心血管疾病中的应用.
- 为了比较现有的工具和指导方法选择.
主要方法:
- 描述用于网络重建和分析的计算技术.
- 对现有的生物信息学工具进行批判性比较.
- 网络重建的说明性例子 (监管,共同表达,PPI).
主要成果:
- 同表达网络对于功能注释是有用的.
- 定向网络有助于推断监管协会.
- 网络重建需要组织特异性和疾病特异性方法,考虑到翻译后的修改.
结论:
- 蛋白质网络分析为心血管疾病提供了宝贵的见解.
- 将网络发现与单细胞RNA测序相结合,可以提高解释能力.
- 定制的网络方法对于有效的生物标志物和药物标识是必不可少的.
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