iTraNet:基于网络的跨组学网络可视化综合分析平台。

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Bioinformatics advances Pub Date : 2024-09-30 eCollection Date: 2024-01-01 DOI:10.1093/bioadv/vbae141
Hikaru Sugimoto, Keigo Morita, Dongzi Li, Yunfan Bai, Matthias Mattanovich, Shinya Kuroda
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引用次数: 0

摘要

动机生物网络的可视化和分析在了解生命系统方面发挥着至关重要的作用。生物网络包括多种类型,从基因调控网络、蛋白质-蛋白质相互作用到代谢网络。代谢网络包括底物、产物和酶,它们受到异构机制和基因表达的调控。然而,由于数据库的多样性和网络分析的复杂性,对这些不同类型的 omics 进行分析具有挑战性:我们开发了 iTraNet,它是一种网络应用程序,用于可视化和分析涉及四种类型网络的跨组学网络:基因调控网络、蛋白质-蛋白质相互作用、代谢网络和代谢物交换网络。利用 iTraNet,我们发现在野生型小鼠中,网络内的枢纽分子倾向于对葡萄糖给药做出反应,而在肥胖/肥胖小鼠中,这种倾向消失了。由于 iTraNet 能够促进网络分析,我们预计它将帮助研究人员深入了解生命系统。可用性和实施:iTraNet 可在 https://itranet.streamlit.app/ 上获取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
iTraNet: a web-based platform for integrated trans-omics network visualization and analysis.

Motivation: Visualization and analysis of biological networks play crucial roles in understanding living systems. Biological networks include diverse types, from gene regulatory networks and protein-protein interactions to metabolic networks. Metabolic networks include substrates, products, and enzymes, which are regulated by allosteric mechanisms and gene expression. However, the analysis of these diverse omics types is challenging due to the diversity of databases and the complexity of network analysis.

Results: We developed iTraNet, a web application that visualizes and analyses trans-omics networks involving four types of networks: gene regulatory networks, protein-protein interactions, metabolic networks, and metabolite exchange networks. Using iTraNet, we found that in wild-type mice, hub molecules within the network tended to respond to glucose administration, whereas in ob/ob mice, this tendency disappeared. With its ability to facilitate network analysis, we anticipate that iTraNet will help researchers gain insights into living systems.

Availability and implementation: iTraNet is available at https://itranet.streamlit.app/.

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