现象义务：一种酶促反应推断的多媒体网络可视化网络服务器
PhenoMultiOmics: an enzymatic reaction inferred multi-omics network visualization web server
影响因子:5.40000
分区:生物学3区 / 生化研究方法3区 生物工程与应用微生物3区 数学与计算生物学3区
发表日期:2024 Nov 01
作者:
Yuying Shi, Botao Xu, Zhe Wang, Qitao Chen, Jie Chai, Cheng Wang
摘要
酶促反应在调节具有高度特异性生物学功能的细胞过程中起关键作用。当疾病中的基因，蛋白质或代谢产功能障碍破坏酶促反应时，可视化产生的扰动酶促反应引起的多摩学网络至关重要。多词网络可视化有助于对生物系统中的功能和调节机制进行全面的了解。在这项研究中，我们设计了现象兴奋剂，这是一种基于酶促反应的多摩斯网络服务器，旨在探索各种癌症类型的多摩学网络的范围。我们首先策划了现象学数据库，该数据库可以基于酶促反应来检索癌症蛋白质 - 金代谢物的关系。然后，我们开发了多组学网络可视化模块，以描述基因，蛋白质和代谢物之间的相互作用，以响应特定的癌症相关酶促反应。生物标志物发现模块通过差异OMIC特征表达和途径富集分析促进了功能分析。现象义务学已应用于分析胃癌的转录组学数据和肺癌的代谢组学数据，为中断的酶促反应提供机械洞察力和相关的多摩学网络。PhenoMicsNetwork。
Abstract
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.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.PhenoMultiOmics is freely accessed at https://phenomultiomics.shinyapps.io/cancer/ with a user-friendly and interactive web interface.