一个可扩展的、基于web的蛋白质组学数据处理、结果存储和分析平台。

IF 3.6 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Journal of Proteome Research Pub Date : 2025-03-07 Epub Date: 2025-02-21 DOI:10.1021/acs.jproteome.4c00871
Markus Schneider, Daniel P Zolg, Patroklos Samaras, Samia Ben Fredj, Dulguun Bold, Agnes Guevende, Alexander Hogrebe, Michelle T Berger, Michael Graber, Vishal Sukumar, Lizi Mamisashvili, Igor Bronsthein, Layla Eljagh, Siegfried Gessulat, Florian Seefried, Tobias Schmidt, Martin Frejno
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引用次数: 0

摘要

蛋白质组学数据的指数增长对传统的处理工作流程提出了严峻的挑战。这些管道通常由零散的软件包组成,使用复杂的内部脚本或在本地硬件上运行的容易出错的手动工作流粘合在一起,维护和扩展成本很高。MSAID平台提供了一个完全自动化的、可管理的蛋白质组学数据管道,将以前脱节的功能整合到统一的api驱动服务中,涵盖从原始数据到生物学见解的整个过程。该平台以云原生搜索算法CHIMERYS以及可扩展的云计算实例和数据湖为支持,促进了大型数据集的高效处理,通过命令行自动化处理,系统的结果存储,分析和可视化。数据湖支持弹性增长的存储和统一查询功能,促进大规模分析和有效重用先前处理过的数据,例如聚合纵向获取的研究。用户通过web界面、CLI客户端或API与平台交互,提供灵活、自动化的访问。访问结果数据的现成工具包括基于浏览器的查询和用于统计分析的一键可视化。该平台简化了研究过程,为更广泛的科学家提供了先进和自动化的蛋白质组工作流程。MSAID平台可通过https://platform.msaid.io在全球范围内使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A Scalable, Web-Based Platform for Proteomics Data Processing, Result Storage and Analysis.

A Scalable, Web-Based Platform for Proteomics Data Processing, Result Storage and Analysis.

A Scalable, Web-Based Platform for Proteomics Data Processing, Result Storage and Analysis.

A Scalable, Web-Based Platform for Proteomics Data Processing, Result Storage and Analysis.

The exponential increase in proteomics data presents critical challenges for conventional processing workflows. These pipelines often consist of fragmented software packages, glued together using complex in-house scripts or error-prone manual workflows running on local hardware, which are costly to maintain and scale. The MSAID Platform offers a fully automated, managed proteomics data pipeline, consolidating formerly disjointed functions into unified, API-driven services that cover the entire process from raw data to biological insights. Backed by the cloud-native search algorithm CHIMERYS, as well as scalable cloud compute instances and data lakes, the platform facilitates efficient processing of large data sets, automation of processing via the command line, systematic result storage, analysis, and visualization. The data lake supports elastically growing storage and unified query capabilities, facilitating large-scale analyses and efficient reuse of previously processed data, such as aggregating longitudinally acquired studies. Users interact with the platform via a web interface, CLI client, or API, providing flexible, automated access. Readily available tools for accessing result data include browser-based interrogation and one-click visualizations for statistical analysis. The platform streamlines research processes, making advanced and automated proteomic workflows accessible to a broader range of scientists. The MSAID Platform is globally available via https://platform.msaid.io.

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来源期刊
Journal of Proteome Research
Journal of Proteome Research 生物-生化研究方法
CiteScore
9.00
自引率
4.50%
发文量
251
审稿时长
3 months
期刊介绍: Journal of Proteome Research publishes content encompassing all aspects of global protein analysis and function, including the dynamic aspects of genomics, spatio-temporal proteomics, metabonomics and metabolomics, clinical and agricultural proteomics, as well as advances in methodology including bioinformatics. The theme and emphasis is on a multidisciplinary approach to the life sciences through the synergy between the different types of "omics".
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