ProVision

ProVision analyzes label-free and TMT-based proteomics data to perform quality control, differential expression analysis, enrichment analyses, and protein–protein interaction prediction for biological interpretation.

Key Features:

• Label-free and TMT workflow support: Processes both label-free and tandem mass tag (TMT)-based proteomics datasets for comparative analysis.
• Quality control: Provides customizable quality control measures and visualizations to assess data integrity.
• Differential expression analysis: Generates differential expression analyses and plots for protein-level comparisons.
• Enrichment analysis: Performs enrichment analyses to identify overrepresented pathways or functional categories.
• Protein–protein interaction prediction: Predicts potential protein–protein interactions to aid interpretation of biological pathways.

Scientific Applications:

• Biomarker discovery: Supports identification of candidate protein biomarkers from comparative proteomics datasets.
• Disease mechanism investigation: Facilitates analysis of protein expression changes to explore disease-associated molecular mechanisms.
• Cellular process characterization: Enables exploration of altered cellular processes and pathways at the protein level.

Methodology:

Implemented in R-shiny and integrates with existing proteomics data analysis pipelines.