Insights in RNA Bioinformatics

RNA bioinformatics has become central to understanding RNA as a versatile regulator of gene expression, cellular organization and disease processes. Advances in high-throughput sequencing, transcriptomics, structural biology and molecular profiling have revealed a complex RNA landscape extending well beyond protein-coding messenger RNA. However, challenges remain in accurately assembling and quantifying transcripts, identifying functional non-coding RNAs, predicting RNA structures and interpreting the effects of RNA modifications and RNA-protein interactions. Recent studies have demonstrated the value of integrating multiple data types with machine learning, language models and experimental evidence to improve RNA annotation, structural prediction and regulatory modelling. Nevertheless, differences between datasets, limited training resources, computational demands and insufficiently standardized benchmarks continue to restrict reproducibility and biological interpretation. Further investigation is therefore needed to connect computational predictions with RNA mechanisms, cellular functions, disease phenotypes and therapeutic opportunities.This Research Topic aims to provide an overview of recent advances in RNA bioinformatics and to examine how computational methods are expanding the study of RNA biology. It will address how transcriptome analysis, structure prediction, modification mapping and regulatory modelling can be integrated to explain RNA production, processing, folding, localization and function. The Research Topic will also consider how artificial intelligence and data-driven approaches can improve the accuracy, scalability and interpretability of RNA analysis. Contributions may explore current limitations, evaluate emerging methodologies and identify priorities for developing reliable, accessible and experimentally relevant computational frameworks.To gather further insights into computational approaches for analyzing RNA sequence, structure, regulation and function, this Research Topic welcomes contributions addressing, but not limited to, the following themes:• Transcriptome assembly, transcript quantification and differential expression analysis• Discovery, annotation and functional characterization of non-coding RNAs• RNA secondary and tertiary structure prediction• Comparative and evolutionary RNA bioinformatics• RNA modifications and epitranscriptomic analysis• RNA-protein interactions and post-transcriptional regulatory elements• RNA localization, stability, processing and translation• Machine learning, deep learning and language models for RNA research• Multimodal integration of transcriptomic, structural and molecular data• RNA bioinformatics applications in disease biology and therapeutic development• Open, reproducible and scalable tools for RNA analysis• Community standards, datasets, validation strategies and benchmarking frameworksThis collection welcomes contributions reflecting on current developments and plotting pathways for upcoming research, from Editorial Board Members of the section, from authors they refer, and, on invitation, from a small number of external researchers whose work is shaping the direction of the field. Authors are encouraged to engage critically with their fields, identify the current challenges and propose novel solutions that advance bioinformatics tools and their application to real biological problems. Topic editors: Dwijesh Chandra Mishra, Kunqi Chen Source: https://www.frontiersin.org/research-topics/86483/insights-in-rna-bioinformatics