Explore synergistic and competitive miRNA regulation mechanisms in the miRNA-mRNA regulatory network from the information decomposition perspective
pan, c.
Show abstract
Since multiple microRNAs can target 3 untranslated regions of the same mRNA transcript, it is likely that these endogenous microRNAs may form synergistic alliances, or compete for the same mRNA harbouring overlapping binding site matches. Synergistic and competitive microRNA regulation is an intriguing yet poorly elucidated mechanism. We here introduce a computational method based on the multivariate information measurement to quantify such implicit interaction effects between microRNAs. Our informatics method of integrating sequence and expression data is designed to establish the functional correlation between microRNAs. To demonstrate our method, we exploited TargetScan and The Cancer Genome Atlas data. As a result, we indeed observed that the microRNA pair with neighbouring binding site(s) on the mRNA is likely to trigger synergistic events, while the microRNA pair with overlapping binding site(s) on the mRNA is likely to cause competitive events, provided that the pair of microRNAs has a high functional similarity and the corresponding triplet presents a positive/negative synergy-redundancy score.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- CancerMIRNome: an interactive analysis and visualization database for miRNome profiles of human cancer 95%
- EuRBPDB: a comprehensive resource for annotation, functional and oncological investigation of eukaryotic RNA binding proteins (RBPs) 95%
- Summarizing internal dynamics boosts differential analysis and functional interpretation of super enhancers 94%
Similar papers in this journal
- Normalizing single-cell RNA sequencing data with internal spike-in-like genes 95%
- tRForest: a novel random forest-based algorithm for tRNA-derived fragment target prediction 94%
- A computational approach for deciphering the interactions between proximal and distal regulators in B cell differentiation 94%
Similar papers in this journal
- Joint reconstruction of cis-regulatory interaction networks across multiple tissues using single-cell chromatin accessibility data 94%
- Predicting Differentially Methylated Cytosines in TET and DNMT3 Knockout Mutants via a Large Language Model 93%
- CoRegNet: Unraveling Gene Co-regulation Networks from Public RNA-Seq Repositories Using a Beta-Binomial Statistical Model 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.