Mei Lang

mRNA design, RNA structure prediction, RNA language model.

I develop RNA and mRNA foundation models for regulatory sequence understanding, RNA structure prediction, and AI-guided therapeutic design, with a focus on mRNA optimization, RNA–RNA interactions, and rigorous downstream biological benchmarks.

Research focus

RNA language models
Developing language models for mRNA and non-coding RNA to learn sequence, structure and regulatory grammar from large-scale RNA data.
mRNA optimization
Designing and optimizing coding regions and UTR regulatory regions to improve mRNA sequence properties and support programmable mRNA design.
RNA structure prediction
Predicting structures of RNA monomers and RNA complexes, with emphasis on RNA folding, RNA–RNA interactions and structure-guided modeling.

Experience and education

PhD Candidate · University of Macau / Hangzhou Institute of Medicine, Chinese Academy of Sciences
AI for life science and RNA/mRNA language modeling.
Research Assistant · Shenzhen Bay Laboratory
RNA language modeling and RNA structure prediction.
MSc · Southwest Jiaotong University
Bioinformatic.
Software Test Engineer · Chinasoft International
After BSc graduation · software testing for router hardware modules in Huawei Wireless Business Unit.
BSc · Yunnan University
Network Engineering.

Selected projects

RNA-MSM
Multiple sequence alignment-based RNA language model for RNA structural inference, including secondary structure and solvent accessibility prediction.
SPOT-RNAc
Benchmarking and prediction framework for RNA–RNA complex interactions using base pairs derived from 3D RNA complex structures.
CodonMamba
Bidirectional Mamba-based codon language model for host-adaptive codon optimization and mRNA sequence design.
3UTRESM
3′UTR foundation model for mRNA regulatory tasks, including degradation prediction, RNA modification prediction and RNA-protein interaction prediction.

Publications

Selected publications sorted by publication time from newest to oldest. # indicates first author or equal contribution.

From foundation models to autonomous agents in biology
Shenghui Huang, Mei Lang, Zihan Chen, Chenxu Yang, Xiaoying Huang, Zeynab Mohtashaminia, Yuzhong Peng. Genomics Communications, 2026, 3:e006. DOI: 10.48130/gcomm-0026-0005.
Benchmarking the methods for predicting base pairs in RNA–RNA interactions
Mei Lang#, Thomas Litfin, Ke Chen, Jun Zhan, Yaoqi Zhou. Bioinformatics, 2025, 41(6):btaf289. Citations: 5.
Multiple sequence alignment-based RNA language model and its application to structural inference
Yikun Zhang#, Mei Lang#, Jiuhong Jiang, Zhiqiang Gao, Fan Xu, Thomas Litfin, Ke Chen, Jaswinder Singh, Xiansong Huang, et al. Nucleic Acids Research, 2024, 52(1):e3–e3. Citations: 137.
Predicting RNA structures and functions by artificial intelligence
Jun Zhang#, Mei Lang#, Yaoqi Zhou, Yang Zhang. Trends in Genetics, 2024, 40(1):94–107. Citations: 49.
Deep learning models of RNA base-pairing structures generalize to unseen folds and make accurate zero-shot predictions of base-base interactions of RNA complexes
Mei Lang#, Thomas Litfin, Ke Chen, Jun Zhan, Yaoqi Zhou. bioRxiv, 2023.09.26.559463. Citations: 1.
Tfcancer: a manually curated database of transcription factors associated with human cancers
Qianwen Huang, Ziyi Tan, Yuting Li, Wei Wang, Mei Lang, Chao Li, Zhi Guo. Bioinformatics, 2021, 37(22):4288–4290. Citations: 8.
EnhFFL: a database of enhancer mediated feed-forward loops for human and mouse
Rui Kang, Ziyi Tan, Mei Lang, Lijin Jin, Yuting Zhang, Yusen Zhang, Tianyun Guo, Zhi Guo. Precision Clinical Medicine, 2021, 4(2):129–135. Citations: 10.

Full citation list: Google Scholar profile.

Awards

Oral Presentation Award
2025 International Graduates Academic Forum on AI + Innovative Drug Research.
Outstanding Employee
Shenzhen Bay Laboratory.

Contact

Email: yc48617@connect.um.edu.mo
GitHub: github.com/meilanglang
Google Scholar: Mei Lang
Website: meilanglang.github.io