ReviewExperimental & molecular medicine2025
Computational methods for alternative polyadenylation and splicing in post-transcriptional gene regulation.
Review in Experimental & molecular medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Review
- SNRPD2-CPSF7-UBE2K axis drives ovarian cancer progression via alternative splicing-polyadenylation crosstalk.Oncogene · 2026Article
- Nanopore direct RNA sequencing and the epitranscriptome: Advances in mapping native RNA landscapes.iMeta · 2026Review
- Benchmarking computational methods for identifying and quantifying polyadenylation sites from 3' tag-based single-cell RNA-seq data.Nucleic acids research · 2026Article
- miRNA regulation in brain tissue space: the 3'UTR perspective.RNA (New York, N.Y.) · 2026Review
- EpGAT: integrating epigenetics and 3D genome structure to predict alternative splicing and polyadenylation.Briefings in bioinformatics · 2026Article
- PolyA-GLM: A comprehensive framework forComputational and structural biotechnology journal · 2026Article
- IPScan: Detecting novel intronic PolyAdenylation events with RNA-seq data.PLoS computational biology · 2025Article
- Conservation and Remodeling of Alternative Splicing Landscapes in the Evolution ofPlants (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Alternative polyadenylation (APA) and alternative splicing (AS) are essential post-transcriptional mechanisms that enhance transcriptome diversity and regulate gene expression across various biological contexts. APA modifies transcript stability, localization and translation efficiency by generating mRNA isoforms with distinct 3' untranslated regions or coding sequences, while AS alters protein diversity through exon inclusion or exclusion. The advent of high-throughput RNA sequencing has driven the development of computational methods to systematically identify, quantify and analyze APA and AS events, shedding light on their regulatory roles in normal physiology and disease. These methods can be broadly categorized based on their underlying methodologies and the data types they process, with specialized tools designed for both bulk and single-cell RNA sequencing. Here, in this Review, we provide a comprehensive overview of computational strategies for APA and AS detection and differential analysis, highlighting their advantages, limitations and applications. In addition, we explore techniques specifically tailored for single-cell RNA sequencing. We enhance our understanding of APA and AS regulation across diverse biological systems by summarizing recent advancements, offering new insights into gene regulation at both the population and single-cell levels.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.