褚晏伊--中国科学院分子细胞科学卓越创新中心

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褚晏伊
研究员，研究组长，博士生导师
E-mail: yanyi.chu@sibcb.ac.cn
实验室主页:

个人简介：

博士毕业于上海交通大学，同时于加拿大 University of Calgary 联合培养，获致远荣誉博士学位，本科毕业于沈阳药科大学。曾在斯坦福大学、普林斯顿大学和Arc Institute从事博士后研究工作。自2026年起任中国科学院分子细胞科学卓越创新中心（生物化学与细胞生物学研究所）研究员，研究组长，博士生导师。

社会任职：

研究方向：

人工智能驱动的 RNA 免疫调控与治疗设计

研究工作：

RNA分子及其调控元件在免疫应答和免疫治疗中发挥着关键作用，其序列、结构和翻译调控特性直接影响免疫分子的表达水平和功能效应。然而，RNA功能的复杂性以及免疫系统的高度异质性，使得RNA免疫治疗的设计长期依赖经验探索，缺乏系统性的设计原则。
本课题组聚焦“人工智能驱动的RNA免疫调控与治疗设计”，围绕mRNA、环状RNA、自复制RNA，研究RNA序列-结构-翻译-免疫效应之间的调控规律。通过结合人工智能方法、计算生物学与免疫学，采用计算分析与实验验证相结合的研究策略，我们将：
（1）系统解析 RNA 非编码调控元件在不同细胞类型和免疫环境中的功能特性，揭示其对 RNA 翻译效率、稳定性和免疫效应的调控机制。
（2）开发人工智能模型，实现RNA调控元件和免疫分子编码序列的理性设计与多目标优化，提升 RNA 在免疫治疗中的表达效率与功能可控性。
（3）探索RNA在个性化新抗原疫苗、CAR-T等免疫治疗模式中的应用，研究免疫分子工程化设计的关键计算原则与方法。
本课题组致力于发展兼具基础机制研究与工程设计潜力的交叉研究方向，为RNA免疫治疗和精准免疫调控提供新的理论基础与技术手段。欢迎具有生物学、免疫学、计算生物学及人工智能背景的学生和研究人员加入。

承担科研项目情况：

代表论著：

1. Yanyi Chu, Dan Yu, Yupeng Li, Kaixuan Huang, Yue Shen, Le Cong, Jason Zhang, and Mengdi Wang, A 5'UTR Language Model for Decoding Untranslated Regions of mRNA and Function Predictions, Nature Machine Intelligence, https://doi.org/10.1038/s42256-024-00823-9
2. Yanyi Chu, Yan Zhang, Qiankun Wang, Lingfeng Zhang, Xuhong Wang, Yanjing Wang, Dennis Russell Salahub, Qin Xu, Jianmin Wang, Xue Jiang, Yi Xiong, Dong-Qing Wei, A transformer-based model to predict peptide-HLA class I binding and optimize mutated peptides for vaccine design, Nature Machine Intelligence, Volume 4, 23 March 2022, Pages 300-311, https://doi.org/10.1038/s42256-022-00459-7
3. Yanyi Chu, Xuhong Wang, Qiuying Dai, Yanjing Wang, Qiankun Wang, Shaoliang Peng, Xiaoyong Wei, Jingfei Qiu, Dennis Russell Salahub, Yi Xiong, Dong-Qing Wei, MDA-GCNFTG: identifying miRNA-disease associations based on graph convolutional networks via graph sampling through the feature and topology graph, Briefings in Bioinformatics, Volume 22, Issue 6, November 2021, bbab165, https://doi.org/10.1093/bib/bbab165
4. Yanyi Chu, Xiaoqi Shan, Tianhang Chen, Mingming Jiang, Yanjing Wang, Qiankun Wang, Dennis Russell Salahub, Yi Xiong, Dong-Qing Wei, DTI-MLCD: predicting drug-target interactions using multi-label learning with community detection method, Briefings in Bioinformatics, Volume 22, Issue 3, May 2021, bbaa205, https://doi.org/10.1093/bib/bbaa205
5. Yanyi Chu, Aman Chandra Kaushik, Xiangeng Wang, Wei Wang, Yufang Zhang, Xiaoqi Shan, Dennis Russell Salahub, Yi Xiong, Dong-Qing Wei, DTI-CDF: a cascade deep forest model towards the prediction of drug-target interactions based on hybrid features, Briefings in Bioinformatics, Volume 22, Issue 1, January 2021, Pages 451–462, https://doi.org/10.1093/bib/bbz152
6. Xueying Mao, Yanyi Chu, Dong-Qing Wei. Designed with interactome-based deep learning. Nat Chem Biol 20, 1399–1401 (2024). https://doi.org/10.1038/s41589-024-01754-7
7. Kaixuan Huang, Yukang Yang, Kaidi Fu, Yanyi Chu, Le Cong, and Mengdi Wang, Latent diffusion models for controllable rna sequence generation, arXiv preprint arXiv:2409.09828, https://arxiv.org/abs/2409.09828
8. Mengyang Liu, Yanyi Chu, Huan Liu, Yuqing Su, Qi Zhang, Jiao Jiao, Mingqi Liu, Junqiang Ding, Min Liu, Yawei Hu, Yueying Dai, Rongping Zhang, Xinrong Liu, Yihui Deng, Yanzhi Song, Accelerated Blood Clearance of Nanoemulsions Modified with PEG-Cholesterol and PEG-Phospholipid Derivatives in Rats: The Effect of PEG-Lipid Linkages and PEG Molecular Weights, Molecular pharmaceutics, Volume 17, Issue 4, April 2020, Pages 1059–1070, https://doi.org/10.1021/acs.molpharmaceut.9b00770
9. Zhiwen Shi, Yanyi Chu, Yonghong Zhang, Yanjing Wang, Dong-Qing Wei, Prediction of Blood-Brain Barrier Permeability of Compounds by Fusing Resampling Strategies and eXtreme Gradient Boosting, IEEE Access, Volume 9, December 2020, Pages 9557-9566, http://doi.org/10.1109/ACCESS.2020.3047852
10. Qiuying Dai, Yanyi Chu, Zhiqi Li, Yusong Zhao, Xueying Mao, Yanjing Wang, Yi Xiong, Dong-Qing Wei, MDA-CF: Predicting MiRNA-Disease associations based on a cascade forest model by fusing multi-source information, Computers in Biology and Medicine, Volume 136, September 2021, 104706, https://doi.org/10.1016/j.compbiomed.2021.104706
11. Tianhang Chen, Xiangeng Wang, Yanyi Chu, Yanjing Wang, Mingming Jiang, Dong-Qing Wei, Yi Xiong, T4SE-XGB: Interpretable Sequence-Based Prediction of Type IV Secreted Effectors Using eXtreme Gradient Boosting Algorithm, Frontiers in Microbiology, Volume 11, Article 580382, September 2020, https://doi.org/10.3389/fmicb.2020.580382
12. Shenggeng Lin, Yanjing Wang, Lingfeng Zhang, Yanyi Chu, Yatong Liu, Yitian Fang, Mingming Jiang, Qiankun Wang, Bowen Zhao, Yi Xiong, Dong-Qing Wei, MDF-SA-DDI: predicting drug-drug interaction events based on multi-source drug fusion, multi-source feature fusion and transformer self-attention mechanism, Briefings in Bioinformatics, Article bbab421, October 2021, https://doi.org/10.1093/bib/bbab421
13. Xiaoqi Shan, Xiangeng Wang, Cheng-dong Li, Yanyi Chu, Yufang Zhang, Yi Xiong, and Dong-Qing Wei, Prediction of CYP450 Enzyme–Substrate Selectivity Based on the Network-Based Label Space Division Method, Journal of Chemical Information and Modeling, Volume 59, Issue 11, October 2019, Pages 4577-4586, https://doi.org/10.1021/acs.jcim.9b00749
14. Yufang Zhang, Xiangeng Wang, Aman Chandra Kaushik, Yanyi Chu, Xiaoqi Shan, Ming-Zhu Zhao, Qin Xu, Dong-Qing Wei, SPVec: A Word2vec-Inspired Feature Representation Method for Drug-Target Interaction Prediction, Frontiers in Chemistry, Volume 7, January 2020, Pages 895, https://doi.org/10.3389/fchem.2019.00895
15. Mingming Jiang, Bowen Zhao, Shenggan Luo, Qiankun Wang, Yanyi Chu, Tianhang Chen, Xueying Mao, Yatong Liu, Yanjing Wang, Xue Jiang, Dong-Qing Wei, Yi Xiong, NeuroPpred-Fuse: an interpretable stacking model for prediction of neuropeptides by fusing sequence information and feature selection methods, Briefings in Bioinformatics, Volume 22, Issue 6, November 2021, bbab310, https://doi.org/10.1093/bib/bbab310

个人简介：

社会任职：

研究方向：

研究工作：

承担科研项目情况：

代表论著：

获奖及荣誉：

研究组成员：