...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Current drug metabolism >Mathematical methods to analysis of topology, functional variability and evolution of metabolic systems based on different decomposition concepts.
【24h】

Mathematical methods to analysis of topology, functional variability and evolution of metabolic systems based on different decomposition concepts.

机译：基于不同分解概念的代谢系统拓扑，功能变异性和进化的数学方法。

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Complexity of metabolic systems can be undertaken at different scales (metabolites, metabolic pathways, metabolic network map, biological population) and under different aspects (structural, functional, evolutive). To analyse such a complexity, metabolic systems need to be decomposed into different components according to different concepts. Four concepts are presented here consisting in considering metabolic systems as sets of metabolites, chemical reactions, metabolic pathways or successive processes. From a metabolomic dataset, such decompositions are performed using different mathematical methods including correlation, stiochiometric, ordination, classification, combinatorial and kinetic analyses. Correlation analysis detects and quantifies affinities/oppositions between metabolites. Stoichiometric analysis aims to identify the organisation of a metabolic network into different metabolic pathways on the hand, and to quantify/optimize the metabolic flux distribution through the different chemical reactions of the system. Ordination and classification analyses help to identify different metabolic trends and their associated metabolites in order to highlight chemical polymorphism representing different variability poles of the metabolic system. Then, metabolic processes/correlations responsible for such a polymorphism can be extracted in silico by combining metabolic profiles representative of different metabolic trends according to a weighting bootstrap approach. Finally evolution of metabolic processes in time can be analysed by different kinetic/dynamic modelling approaches.
机译：代谢系统的复杂性可以在不同的规模（代谢物，代谢途径，代谢网络图，生物种群）和不同方面（结构，功能，进化）下进行。为了分析这种复杂性，需要根据不同的概念将代谢系统分解为不同的成分。这里介绍了四个概念，其中包括将代谢系统视为一组代谢产物，化学反应，代谢途径或连续过程。从代谢组学数据集中，可以使用不同的数学方法（包括相关性，化学计量学，排序，分类，组合和动力学分析）执行此类分解。相关分析可检测和量化代谢物之间的亲和力/相对性。化学计量分析的目的是识别代谢网络在手上的不同代谢途径中的组织，并通过系统的不同化学反应来量化/优化代谢通量分布。排序和分类分析有助于识别不同的代谢趋势及其相关代谢产物，以突出显示代表代谢系统不同可变性极点的化学多态性。然后，可以根据加权自举方法，通过组合代表不同代谢趋势的代谢谱，以计算机方式提取负责这种多态性的代谢过程/相关性。最后，可以通过不同的动力学/动力学建模方法来分析代谢过程的及时演变。

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