...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Applied Network Science >Guideline for comparing functional enrichment of biological network modular structures
【24h】

Guideline for comparing functional enrichment of biological network modular structures

机译：比较生物网络模块结构功能丰富性的指南

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Abstract The use of networks to analyze biological data, such as large gene or protein expression datasets, is on the rise. Often, there is an interest of identifying modules (or communities) of biological molecules that may be associated to known functions. This functional modularity analyses usually revolve around a workflow that combines 1) a method for network reconstruction from biological data, 2) a community or clustering algorithm on a network, and 3) an enrichment analysis to associate modules to known biological categories. With this, it is possible to identify sets of functions associated to modules in networks of distinct biological conditions, allowing for the comparison of such different phenotypes.Currently there is no set of recommendations for such analyses, which can lead to problems in assessing these results for a given biological context. Furthermore, without properly identifying the methodological scopes and limitations at each stage for a given functional modularity analysis, it is not immediately possible to compare the biological implications of analyses in different phenotypes.In this work, critical points in a functional modularity analysis for biological networks are identified, and methods are proposed for assessing the topological and biological results of functional modularity analyses in biological networks, and to calculate topological and functional similarity between comparable phenotypes. These methods are demonstrated on biological networks artificially constructed from known biological pathways.
机译：摘要使用网络分析生物数据（例如大型基因或蛋白质表达数据集）的趋势正在上升。通常，人们感兴趣的是识别可能与已知功能相关的生物分子模块（或群落）。这种功能模块性分析通常围绕以下工作流程进行：1）一种从生物学数据重建网络的方法，2）网络上的社区或聚类算法，以及3）将模块与已知生物学类别相关联的富集分析。这样一来，就可以识别与不同生物学条件网络中的模块相关的功能集，从而可以比较这些不同的表型。目前尚无针对此类分析的建议集，这可能导致评估这些结果时出现问题在给定的生物学背景下。此外，在没有正确确定给定功能模块分析的每个阶段的方法学范围和局限性的情况下，无法立即比较不同表型的分析的生物学含义。在这项工作中，生物网络功能模块分析的关键点鉴定，并提出了评估生物学网络中功能模块性分析的拓扑和生物学结果，并计算可比较表型之间的拓扑和功能相似性的方法。这些方法在从已知生物学途径人工构建的生物学网络上得到证明。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号