ceRNAnetsim

ceRNAnetsim simulates and analyzes competing endogenous RNA (ceRNA) networks and their interactions with microRNAs (miRNAs) to model network-wide regulatory effects arising from expression perturbations.

Key Features:

• Network-based model: ceRNAnetsim integrates miRNA:ceRNA interactions with expression values to calculate network-wide effects resulting from perturbations in node expression.
• Incorporation of miRNA interaction factors: The tool considers seed type and binding energy to quantify miRNA:target interactions.
• Scalability and flexibility: Accommodates emerging miRNA effectors including circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs).
• Sponge effect modeling: Accounts for ceRNA-mediated sequestration of miRNAs and consequent modulation of miRNA availability to target mRNAs.
• Large-scale network analysis: Applied to large-scale miRNA:target networks from breast cancer patient data to identify highly perturbing genes that coincide with known breast cancer-associated genes and miRNAs.

Scientific Applications:

• Cancer research: Analyzing miRNA:ceRNA interactions in the context of cancer to uncover regulatory mechanisms and potential biomarkers associated with disease progression.
• Gene regulation studies: Providing insights into crosstalk between non-coding RNAs to aid understanding of gene regulation at a network level.
• Identification of regulatory pathways: Simulating changes in expression and observing resultant network effects to identify regulatory pathways evident only within the broader network context.

Methodology:

ceRNAnetsim uses a network-based computational model that integrates miRNA:ceRNA interactions with expression values, incorporates miRNA interaction factors (seed type and binding energy), simulates perturbations in expression levels to compute propagated network effects, models ceRNA sponge effects, and has been applied to large-scale miRNA:target networks from breast cancer patient data.