Exploring RNA Biology with Deep Learning Algorithms
The RNA biology journal is launching a new open‑access article collection called “Exploring RNA Biology with Deep Learning Algorithms” to bring together the latest breakthroughs at the intersection of transcriptomics, RNA structure prediction, molecular design and AI‑driven approaches.
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.
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:
- Prof. Yiliang Ding (John Innes Centre): Pioneer of in vivo RNA structure mapping and chemical probing methods
- Prof. Qiangfeng Cliff Zhang (Tsinghua University): Specialist in AI‑informed big‑data analysis
Details & Submission
Join the Conversation
Have questions about a potential submission, or want to discuss a cutting‑edge idea? Feel free to reach out via the contact form on this site or connect with me on LinkedIn.