PhenoMultiOmics: an enzymatic reaction inferred multi-omics network visualization web server.

Yuying Shi, Botao Xu, Zhe Wang, Qitao Chen, Jie Chai, Cheng Wang
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Abstract

Motivation: Enzymatic reaction play a pivotal role in regulating cellular processes with a high degree of specificity to biological functions. When enzymatic reactions are disrupted by gene, protein, or metabolite dysfunctions in diseases, it becomes crucial to visualize the resulting perturbed enzymatic reaction-induced multi-omics network. Multi-omics network visualization aids in gaining a comprehensive understanding of the functionality and regulatory mechanisms within biological systems.

Results: In this study, we designed PhenoMultiOmics, an enzymatic reaction-based multi-omics web server designed to explore the scope of the multi-omics network across various cancer types. We first curated the PhenoMultiOmics database, which enables the retrieval of cancer-gene-protein-metabolite relationships based on the enzymatic reactions. We then developed the MultiOmics network visualization module to depict the interplay between genes, proteins, and metabolites in response to specific cancer-related enzymatic reactions. The biomarker discovery module facilitates functional analysis through differential omic feature expression and pathway enrichment analysis. PhenoMultiOmics has been applied to analyze the transcriptomics data of gastric cancer and the metabolomics data of lung cancer, providing mechanistic insights into interrupted enzymatic reactions and the associated multi-omics network.

Availability and implementation: PhenoMultiOmics is freely accessed at https://phenomultiomics.shinyapps.io/cancer/ with a user-friendly and interactive web interface.

PhenoMultiOmics:酶反应推断多组学网络可视化网络服务器。
动机酶促反应在调节细胞过程中发挥着关键作用,对生物功能具有高度特异性。当疾病中的基因、蛋白质或代谢物功能失调导致酶促反应紊乱时,将酶促反应引起的多组学网络可视化就变得至关重要。多组学网络可视化有助于全面了解生物系统的功能和调控机制:在这项研究中,我们设计了一个基于酶反应的多组学网络服务器 PhenoMultiOmics,旨在探索各种癌症类型的多组学网络范围。我们首先建立了 PhenoMultiOmics 数据库(PMODB),该数据库可根据酶促反应检索癌症基因-蛋白质-代谢物之间的关系。然后,我们开发了 MultiOmics 网络可视化模块,以描述基因、蛋白质和代谢物之间在特定癌症相关酶促反应中的相互作用。生物标记物发现模块通过差异 omic 特征表达和通路富集分析促进功能分析。PhenoMultiOmics 已被用于分析胃癌的转录组学数据和肺癌的代谢组学数据,为中断的酶反应和相关的多组学网络提供了深入的见解:PhenoMultiOmics 可在 https://phenomultiomics.shinyapps.io/cancer/ 免费访问,并提供用户友好的交互式网络界面:补充信息:补充数据可在 Bioinformatics online 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。
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