Exploring RNA Biology with Deep Learning Algorithms

An RNA Biology article collection on deep learning methods in transcriptomics, RNA structure prediction, and molecular design.

I will be serving as Guest Editor for the RNA Biology article collection “Exploring RNA Biology with Deep Learning Algorithms”. My aim is to curate articles that showcase how machine learning models can reveal hidden patterns in sequencing data, predict complex three dimensional RNA shapes with high accuracy and guide the design of novel RNA molecules for both research and therapeutic use.

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Why This Collection Matters

RNA plays a central role in virtually every biological process, from gene regulation to the assembly of protein complexes. Yet its complexity poses formidable analytical challenges. Over the past few years, deep learning has transformed the way we decode protein structures and genomic data. Now, we stand on the edge of a similar revolution in RNA biology:

  • Uncover hidden patterns in high‑throughput sequencing data
  • Predict RNA modifications and their functional impacts
  • Model secondary & tertiary structures with unprecedented accuracy
  • Design synthetic RNAs for therapeutics and synthetic biology
  • Map RNA–protein interactions and regulatory switches at scale

What We’re Looking For

By pooling insights from biochemists, computational biologists and AI specialists, this special issue aims to chart the next frontier in RNA research. We welcome original research, methods papers and in‑depth reviews on topics including (but not limited to):

  • Deep learning for transcriptome analysis
  • AI models of RNA modifications
  • Secondary & tertiary structure prediction
  • AI‑driven RNA design & editing
  • RNA–protein interaction mapping
  • Automated annotation of RNA architectures

Advisory Panel

I’m pleased to be joined by two leading experts in RNA science as Guest Advisors:

Join the Conversation

Questions about a potential submission or a related research idea are always welcome. You can reach me through the contact form or connect with me on LinkedIn.