X2K Web

X2K Web infers upstream regulatory networks from differentially expressed genes to identify transcription factors, protein-protein interactions, and kinases that may drive observed gene expression changes.

Key Features:

• eXpression2Kinases (X2K) algorithm: Implements a refined X2K algorithm to infer upstream regulators from gene expression data.
• Transcription Factor Enrichment Analysis: Performs enrichment analysis to identify transcription factors likely to regulate differentially expressed genes.
• Protein-Protein Interaction (PPI) Network Expansion: Expands identified transcription factors into subnetworks using known protein-protein interactions (PPIs).
• Kinase Enrichment Analysis: Conducts kinase enrichment on members of the PPI-derived subnetwork to identify candidate regulatory kinases.
• Enhanced Libraries and Networks: Incorporates expanded libraries of transcription factors and kinases and updated PPI networks.
• Benchmarking and Optimization: Uses benchmarking with random permutations to identify optimal parameter settings for analyses.

Scientific Applications:

• Cell signaling profiling from mRNA: Profiles activity of cell signaling pathways from mRNA expression data by predicting upstream regulatory networks.
• Regulatory interaction elucidation: Aids in elucidating how transcription factors, proteins, and kinases interact to regulate gene expression.
• Analysis of kinase inhibitor signatures in cancer: Applied to thousands of gene expression signatures induced by kinase inhibitors across six breast cancer cell lines.

Methodology:

Implements a refined X2K workflow that performs transcription factor enrichment, expands TFs into subnetworks via PPIs, conducts kinase enrichment on the subnetwork members, and uses random-permutation benchmarking to optimize parameter settings.