ArticleMethods in molecular biology (Clifton, N.J.)2025
Temporal Expression Analysis to Unravel Gene Regulatory Dynamics by microRNAs.
Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Discovery of a Ferroptosis-Related lncRNA-miRNA-mRNA Gene Signature in Endometrial Cancer Through a Comprehensive Co-Expression Network Analysis.Current oncology (Toronto, Ont.) · 2026Article
- A cell type-specific expression atlas of small and total RNA in the heart after myocardial infarction.Scientific data · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
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Abstract
MicroRNAs (miRNAs) are a class of small non-coding RNAs (sncRNAs) of length 21-25 nucleotides. These sncRNAs hybridize to repress their target genes and inhibit protein translation, thereby controlling regulatory functions in the cell. Integration of time-series matched small and RNA-seq data enables investigation of dynamic gene regulation through miRNAs during development or in response to a stimulus, such as stress. Here we summarize analysis strategies, such as probabilistic and regression-based models, that take advantage of the temporal dimension to investigate the complexity of miRNA regulation.
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Registered trials
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