ProTExA

ProTExA performs post-processing analysis of protein and gene expression datasets using network-based approaches to identify differentially expressed entities, enriched pathways, and molecular interaction networks for proteomics research.

Key Features:

• Differential Expression Analysis: Performs statistical analysis and filtering to identify differentially expressed proteins and genes across samples.
• Enrichment Analysis: Conducts pathway enrichment analysis to determine significantly impacted biological pathways associated with the differentially expressed proteins and genes.
• Network Generation: Generates pathway-to-pathway and pathway-to-gene networks to map interactions between pathways and genes.
• Protein and Gene Co-expression Networks: Constructs co-expression networks to reveal concurrent expression patterns among proteins or genes across samples.
• Clustering Methodologies: Applies clustering to identify sub-networks and groups of co-expressed proteins or genes that may be functionally related.

Scientific Applications:

• Disease mechanism investigation: Characterizes altered proteins, genes, pathways, and interaction networks implicated in disease states.
• Biomarker discovery: Identifies candidate protein or gene biomarkers based on differential expression and network context.
• Gene and pathway function exploration: Illuminates functional relationships among genes and pathways through enrichment and network analyses.
• Proteomics data interpretation: Integrates expression and network information to support interpretation of proteomics datasets.

Methodology:

Uses network-based bioinformatics with statistical analysis and filtering for differential expression, enrichment analysis for pathway significance, generation of pathway-to-pathway and pathway-to-gene networks, construction of protein and gene co-expression networks, and clustering to define sub-networks.