PTRcombiner

PTRcombiner identifies clusters of co-regulating post-transcriptional trans-factors, including RNA binding proteins (RBPs) and microRNAs (miRNAs), from transcriptome-wide pairwise interaction annotations to elucidate combinatorial post-transcriptional regulatory networks.

Key Features:

• Cluster Identification: Extracts clusters of co-regulating RBPs and miRNAs from RNA–protein and RNA–RNA interaction maps using pairwise interaction annotations.
• Biological Characterization: Analyzes overlap among target genes, performs Gene Ontology (GO) enrichment analyses, and assesses GO term similarity to infer functional roles of clusters.
• Binding Site Analysis: Examines positional binding information to evaluate binding site similarity among co-regulators within the same cluster.
• Experimental Validation: Validated on experimental interaction datasets from human and yeast interactions to identify functionally related co-regulatory modules.

Scientific Applications:

• Post-transcriptional regulatory network analysis: Enables identification and characterization of combinatorial interactions among RBPs and miRNAs that modulate gene expression.
• Functional module discovery: Supports discovery of co-regulatory modules and their enriched GO terms for generating biological hypotheses.
• Comparative analysis: Applied to human and yeast datasets to examine conserved or species-specific co-regulatory patterns.

Methodology:

Processes transcriptome-wide RNA–protein and RNA–RNA pairwise interaction annotations to detect clusters of co-regulators, integrates positional binding information, and analyzes clusters using target-overlap metrics, GO enrichment, and GO term similarity.