iProPhos: A Web-Based Interactive Platform for Integrated Proteome and Phosphoproteome Analysis.

IF 6.1 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Molecular & Cellular Proteomics Pub Date : 2024-01-01 Epub Date: 2023-12-12 DOI:10.1016/j.mcpro.2023.100693
Jing Zou, Ziran Qin, Ran Li, Xiaohua Yan, Huizhe Huang, Bing Yang, Fangfang Zhou, Long Zhang
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引用次数: 0

Abstract

Large-scale omics studies have generated a wealth of mass spectrometry-based proteomics data, which provide additional insights into disease biology spanning genomic boundaries. However, there is a notable lack of web-based analysis and visualization tools that facilitate the reutilization of these data. Given this challenge, we present iProPhos, a user-friendly web server to deliver interactive and customizable functionalities. iProPhos incorporates a large number of samples, including 1444 tumor samples and 746 normal samples across 12 cancer types, sourced from the Clinical Proteomic Tumor Analysis Consortium. Additionally, users can also upload their own proteomics/phosphoproteomics data for analysis and visualization. In iProPhos, users can perform profiling plotting and differential expression, patient survival, clinical feature-related, and correlation analyses, including protein-protein, mRNA-protein, and kinase-substrate correlations. Furthermore, functional enrichment, protein-protein interaction network, and kinase-substrate enrichment analyses are accessible. iProPhos displays the analytical results in interactive figures and tables with various selectable parameters. It is freely accessible at http://longlab-zju.cn/iProPhos without login requirement. We present two case studies to demonstrate that iProPhos can identify potential drug targets and upstream kinases contributing to site-specific phosphorylation. Ultimately, iProPhos allows end-users to leverage the value of big data in cancer proteomics more effectively and accelerates the discovery of novel therapeutic targets.

iProPhos:基于网络的综合蛋白质组和磷酸蛋白质组分析互动平台。
大规模的组学研究产生了大量基于质谱的蛋白质组学数据,这些数据提供了对跨越基因组边界的疾病生物学的更多见解。然而,基于网络的分析和可视化工具明显不足,无法促进这些数据的再利用。iProPhos整合了大量样本,包括来自临床肿瘤蛋白质组分析联盟的12种癌症类型的1444个肿瘤样本和746个正常样本。此外,用户还可以上传自己的蛋白质组学/磷蛋白组学数据进行分析和可视化。在 iProPhos 中,用户可以进行剖析图绘制和差异表达、患者生存、临床特征相关和相关性分析,包括蛋白质-蛋白质、mRNA-蛋白质和激酶-底物相关性分析。此外,还可进行功能富集、蛋白-蛋白相互作用网络和激酶-底物富集分析。iProPhos 通过交互式图表和表格显示分析结果,并提供各种可选参数。它可在 http://longlab-zju.cn/iProPhos 免费访问,无需登录。我们介绍了两个案例研究,以证明 iProPhos 可以识别潜在的药物靶点和导致位点特异性磷酸化的上游激酶。最终,iProPhos 使最终用户能够更有效地利用癌症蛋白质组学大数据的价值,并加速发现新的治疗靶点。
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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来源期刊
Molecular & Cellular Proteomics
Molecular & Cellular Proteomics 生物-生化研究方法
CiteScore
11.50
自引率
4.30%
发文量
131
审稿时长
84 days
期刊介绍: The mission of MCP is to foster the development and applications of proteomics in both basic and translational research. MCP will publish manuscripts that report significant new biological or clinical discoveries underpinned by proteomic observations across all kingdoms of life. Manuscripts must define the biological roles played by the proteins investigated or their mechanisms of action. The journal also emphasizes articles that describe innovative new computational methods and technological advancements that will enable future discoveries. Manuscripts describing such approaches do not have to include a solution to a biological problem, but must demonstrate that the technology works as described, is reproducible and is appropriate to uncover yet unknown protein/proteome function or properties using relevant model systems or publicly available data. Scope: -Fundamental studies in biology, including integrative "omics" studies, that provide mechanistic insights -Novel experimental and computational technologies -Proteogenomic data integration and analysis that enable greater understanding of physiology and disease processes -Pathway and network analyses of signaling that focus on the roles of post-translational modifications -Studies of proteome dynamics and quality controls, and their roles in disease -Studies of evolutionary processes effecting proteome dynamics, quality and regulation -Chemical proteomics, including mechanisms of drug action -Proteomics of the immune system and antigen presentation/recognition -Microbiome proteomics, host-microbe and host-pathogen interactions, and their roles in health and disease -Clinical and translational studies of human diseases -Metabolomics to understand functional connections between genes, proteins and phenotypes
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