five

Data_Sheet_1_The Large Scale Structure of Human Metabolism Reveals Resilience via Extensive Signaling Crosstalk.CSV

收藏
NIAID Data Ecosystem2026-03-12 收录
下载链接:
https://figshare.com/articles/dataset/Data_Sheet_1_The_Large_Scale_Structure_of_Human_Metabolism_Reveals_Resilience_via_Extensive_Signaling_Crosstalk_CSV/13384532
下载链接
链接失效反馈
官方服务:
资源简介:
Metabolism is loosely defined as the set of physical and chemical interactions associated with the processes responsible for sustaining life. Two evident features arise whenever one looks at metabolism: first, metabolism is conformed as a very complex and intertwined construct of the many associated biomolecular processes. Second, metabolism is characterized by a high degree of stability reflected by the organisms resilience to either environmental changes or pathogenic conditions. Here we will investigate the relationship between these two features. By having access to the full set of human metabolic interactions as reported in the highly curated KEGG database, we built an integrated human metabolic network comprising metabolic, transcriptional regulation, and protein-protein interaction networks. We hypothesized that a metabolic process may exhibit resilience if it can recover from perturbations at the pathway level; in other words, metabolic resilience could be due to pathway crosstalk which may implicate that a metabolic process could proceed even when a perturbation has occurred. By analyzing the topological structure of the integrated network, as well as the hierarchical structure of its main modules or subnetworks, we observed that behind biological resilience lies an intricate communication structure at the topological and functional level with pathway crosstalk as the main component. The present findings, alongside the advent of large biomolecular databases, such as KEGG may allow the study of the consequences of this redundancy and resilience for the study of healthy and pathological phenotypes with many potential applications in biomedical science.
创建时间:
2020-12-16
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作