MicroRNA in disease regulation

miRDriver identifies copy number-derived miRNA-gene regulatory interactions in cancer using integrated genomic data and outperforms existing methods.

This study compares miRNA profiling methods using synthetic pools and exRNA samples, finding significant differences in reproducibility, accuracy, and sensitivity across platforms.

miRspongeR is an R/Bioconductor package that identifies and analyzes miRNA sponge interaction networks and modules using seven methods and an integrative approach.

The paper measures production and degradation rates of miRNAs in different mouse cell types, revealing rapid duplex production, fast Argonaute loading, and cell-type-dependent half-lives.

This study shows that miR-218 in the medial prefrontal cortex (mPFC) influences resilience or susceptibility to depression-like behaviors in mice and that its expression in blood correlates with mPFC levels.

The paper identifies functional miRNA::mRNA interactions in Drosophila using AGO CLIP experiments and quantifies their impact on gene expression and translation.

The paper introduces a neural network framework, MDA-CNN, for predicting miRNA-disease and miRNA-phenotype associations, showing improved performance over existing methods.

The paper identifies and validates target genes of hsa-miR-548ba and hsa-miR-7973 in granulosa cells, showing their roles in follicle development and extracellular matrix remodeling.

The paper profiles small RNA expression in LPS-stimulated human monocytes and identifies a limited set of miRNAs upregulated during inflammation.

This study identifies miR-142's role in regulating alveolar epithelial cell lineage formation through interactions with the glucocorticoid and p300 signaling pathways.

This paper identifies miRNA-mRNA regulatory relationships in breast cancer using invariant causal prediction and shows improved performance over existing methods.

The paper evaluates miRNA inhibitor efficacy using CE-LIF in A549 cells, showing effective inhibition of miRNA-23a and miRNA-24 at 20 nM.

This study identifies microRNA expression and target sites in 17 bovine tissues, revealing tissue-specific regulation and genomic features of microRNA-target interactions.

The paper shows that trans-splicing of the C. elegans let-7 primary transcript produces an RNA that negatively regulates let-7 microRNA biogenesis and let-7 family microRNA activity.

This study shows that 3' sequence identity is not required for the established function of miR-146a in myeloid cells in vivo.

The paper identifies how miRNAs reinforce PRC2-mediated repression of target genes through feed-forward networks or independent mechanisms.

The paper identifies miRNA clusters driving triple negative breast cancer subtypes using a new computational pipeline and validates their role in promoting the phenotype through proliferation and EMT control.

The paper shows the lin-28-lin-46 pathway regulates HBL-1 nuclear accumulation independently of let-7 microRNAs, contributing to robust cell-fate progression in C. elegans.

RumimiR is a database of microRNAs for ruminant species, providing detailed information on sequences, tissue origins, and experimental conditions.

The paper shows that structural differences in pri-miRNA paralogs lead to alternative Drosha cleavage, generating miRNAs with expanded target repertoires and distinct roles in tumor progression.

This study identifies differentially expressed microRNAs in Alzheimer’s disease across brain, blood, and cerebrospinal fluid through a systematic review and meta-analysis of 147 datasets.

AQ-seq improves miRNA quantification by reducing ligation bias, revealing new miRNA variants and modifications.

miRBaseConverter provides tools to convert and retrieve miRNA information across miRBase versions, addressing inconsistencies in miRNA data.

OMCD provides a web-based database for pan-cancer miRNA expression analysis, enabling visualization, statistical analysis, and exploration of miRNA clusters across cancer types.

The paper predicts plant-derived xenomiRs using random forest and 1D CNN models, identifying 241 potential candidates and analyzing their potential functions in the human body.

The paper investigates how miRNA-mRNA networks regulate cell-type-specific transcriptomes during human brain development using AGO2-HITS-CLIP, single-cell profiling, and bipartite network analysis.

The paper analyzes miRNA-gene positive correlations across 31 cancers using TCGA data, finding their prevalence, clinical relevance, and potential epigenetic mechanisms.

The paper identifies 21 key differentially expressed miRNAs across 14 cancer types using TCGA data, showing their potential as biomarkers and therapeutic targets.

The paper develops ADmiRE to annotate miRNA variants in large population datasets, identifies highly constrained miRNAs, and provides conservation scores for future disease studies.