ProteomeExpert: a Docker image-based web server for exploring, modeling, visualizing and mining quantitative...

Area of Science:

• Bioinformatics
• Computational Biology
• Proteomics

Background:

• High-throughput omics technologies generate large-scale datasets.
• Mass spectrometry-based proteomics, including data-independent acquisition, is increasingly used in clinical studies.
• Analyzing large quantitative proteomic and multi-omics datasets presents computational challenges.

Purpose of the Study:

• To develop an efficient and user-friendly web server-based software tool for analyzing quantitative proteomic and other omics data.
• To provide a comprehensive platform for experimental design, data mining, interpretation, and visualization.
• To facilitate the analysis of large-scale proteomic datasets from clinical studies.

Main Methods:

• Development of ProteomeExpert, a web server-based software tool.
• Implementation using Docker for easy deployment on various operating systems.
• Integration of various analysis tools for quantitative proteomic data.
• Support for R language environment.

Main Results:

• ProteomeExpert offers a suite of tools for comprehensive analysis of quantitative proteomic datasets.
• The software is designed for efficient and convenient handling of large datasets.
• It supports integration with other omics data types like transcriptomics and metabolomics.
• The tool facilitates experimental design, data mining, interpretation, and visualization.

Conclusions:

• ProteomeExpert provides a valuable resource for researchers analyzing large-scale quantitative proteomic and multi-omics data.
• The Docker implementation ensures accessibility and ease of deployment.
• The web server approach enhances convenience for data analysis in clinical and research settings.