DIANA miRPath
DIANA-miRPath v2.0 performs pathway analysis to identify molecular pathways altered by single or multiple microRNAs using DIANA-microT-CDS predictions and TarBase v6 experimental targets.
Key Features:
- High-Accuracy miRNA Target Prediction: Uses the DIANA-microT-CDS algorithm and incorporates experimentally verified targets from TarBase v6 to identify miRNA targets.
- Integration and Meta-analysis: Merges results using advanced meta-analysis algorithms and performs hierarchical clustering of miRNAs and pathways based on interaction levels.
- Visualization: Produces dendrograms and heat maps depicting miRNA versus pathway interactions for interpretation of interaction patterns.
- Pathogenic SNPs Module: Provides information on pathogenic single nucleotide polymorphisms located within miRNA target sites.
- Reverse Search Module: Annotates predicted and experimentally validated miRNA targets within selected molecular pathways.
Scientific Applications:
- Gene Regulation Studies: Enables identification of pathways regulated by individual or combinations of miRNAs.
- Disease Mechanism Elucidation: Supports analysis of miRNA-mediated pathway alterations relevant to disease processes.
- Therapeutic Target Identification: Aids in pinpointing pathway components influenced by miRNAs that may serve as therapeutic targets.
Methodology:
Combines DIANA-microT-CDS predictions with TarBase v6 experimental targets, merges results via meta-analysis algorithms, applies hierarchical clustering, generates dendrograms and heat maps, and incorporates a SNPs module and reverse search annotation.
Topics
Details
- Tool Type:
- web application
- Operating Systems:
- Linux, Windows, Mac
- Added:
- 3/25/2017
- Last Updated:
- 11/24/2024
Operations
Publications
Vlachos IS, Kostoulas N, Vergoulis T, Georgakilas G, Reczko M, Maragkakis M, Paraskevopoulou MD, Prionidis K, Dalamagas T, Hatzigeorgiou AG. DIANA miRPath v.2.0: investigating the combinatorial effect of microRNAs in pathways. Nucleic Acids Research. 2012;40(W1):W498-W504. doi:10.1093/nar/gks494. PMID:22649059. PMCID:PMC3394305.