mirConnX

mirConnX infers genome-wide mRNA–microRNA and transcription factor regulatory networks by integrating sequence information and gene expression data for Homo sapiens and Mus musculus.

Key Features:

• Static network construction: Pre-constructed genome-wide static networks for human and mouse including computationally predicted transcription factor–gene associations and miRNA target predictions supplemented with literature-sourced interactions.
• Dynamic network inference: Accepts user-provided gene expression data to infer dynamic TF–gene and miRNA–gene associations using a user-selected association measure.
• Data integration: Integrates sequence information with gene expression profiles to combine prediction-based and expression-informed regulatory evidence.
• Network integration: Merges static and dynamically inferred networks via a customizable integration function that allows user-specified weighting of components.

Scientific Applications:

• Disease-specific regulatory network analysis: Construction and interrogation of genome-wide TF and miRNA regulatory networks in disease contexts for human and mouse.
• TF–miRNA interaction exploration: Dissection of combined transcriptional and post-transcriptional regulatory effects mediated by transcription factors and miRNAs.
• Hypothesis generation for therapeutic targets and pathogenesis: Identification of candidate regulatory interactions for downstream experimental validation and mechanistic studies.

Methodology:

Combines sequence data with gene expression profiles; builds static networks from computational predictions and literature-sourced interactions; infers dynamic associations from user-supplied expression data using a selectable association measure; integrates static and dynamic networks using a customizable, weighted function.