研究方向

欢迎访问内蒙古大学生物信息学实验室,我们的研究方向主要集中于:
   早期胚胎发育编程与体细胞重编程相关的“数字胚胎”研究: 开发了空间多组学异构切片对齐算法3d-OT,构建了小鼠胚胎发育的3D时空轨迹 (Nature Methods, 2026);提出基于定量描述“Waddington景观”哺乳动物早期胚胎发育和体细胞重编程过程细胞能量状态的方法 (Research, 2023,发明专利ZL 202211397106.0),构建了最全面的哺乳动物多物种“数字发育”多组学资源库EmAtlas(Nucleic Acids Research, 2023)和家畜繁育数据库LivestockDev (Zoological Research, 2025),建立了细胞命运转变的人工智能预测平台EmPredictor(Bioinformatics, 2021; Brief Bioinform. 2021),筛选了全面的体细胞重编程过程胚胎基因组激活(ZGA)的分子屏障与组蛋白协同修饰调控等表观调控障碍 (BBA-Gene Regulatory Mechanisms. 2022a,b; Communications Biology. 2026),完成先锋转录因子竞争性和协同靶向调控细胞重编程的理论生物学描述 (Brief Bioinform. 2021),提出模块化方法从中心法则(DNA-RNA-Protein)层面,解析了三种去甲基化酶家族TET、ALKBH、KDM非同源功能分化和特异性催化DNA,RNA和蛋白质底物适配性规律(Cell Mol Life Sci. 2021; Brief Bioinform. 2019, 2021; ESI 1% 高被引论文)。
   单细胞组学与时空组学多模态数据生物信息学算法研究: 提出一种基于最小离散增量的时序性单细胞轨迹推断的方法IDTI(Fundamental Research. 2024),提出了一种基于EfficientNet卷积神经网络开展时空转录组空间域的方法EfNST(Communications Biology. 2024),构建了首个基于人工智能模型的预测益生菌的方法及平台(Brief Bioinform. 2021, 国家发明专利ZL202211397170.9)针对能否用较少氨基酸类别开展蛋白质序列、结构及功能的分析和从头设计?先后开发了基于氨基酸约化字母表 (RAAC)进行蛋白质功能的人工智能(AI)研究 (Peptides. 2009),搭建了分析与特征提取平台RaacBook (Bioinformatics. 2017; ESI 1% 高被引论文; Database, 2019; 软著2019SR0467812),开发了RaacLogo (Brief Bioinform. 2021; ESI 1% 高被引论文)和RaacFold (Nucleic Acids Research, 2022; 内蒙古人民政府官网报道)。早期工作还包括:发展了基于DNA空间几何描述参数建立启动子机器学习预测模型的方法 (Prog Biochem Biophys 2009; Physica A 2010; Genomics 2011),将离散增量(ID)与K紧邻算法有机结合,先后提出了K 近邻平均离散增量算法K-MID (Amino Acids 2010)和K 近邻最小离散增量算法KNN-ID (Amino Acids. 2013; Mol Biosyst. 2015)等。

最新成果

  Bingjie Dai, Litai Yi, Peizhuo Wang, Hanshuang Li, Pengwei Hu, Yancheng Song, Jixiang Xing, Zhenxing Feng, Zhiyuan Yuan*, Yongchun Zuo*. 3d-OT: A Deep Geometry-aware Framework for Heterogeneous Slices Alignment of Spatial Multi-omics, Nature Methods. 2026, 23:760–771.(IF:28.3).
  Xinyu Zhao, Jie Wu, Yingxue Che, Chunshen Long, Yongqiang Xing, Hanshuang Li*, Yongchun Zuo*.Machine and Deep Learning Reveal Sequence Determinants Encoding Bivalent Histone Modifications, Communications Biology, 2026, 9(1):491. (IF:5.8).
  Hanshuang Li, Chunshen Long, Yan Hong, Liaofu Luo, Yongchun Zuo*. Characterizing Cellular Differentiation Potency and Waddington Landscape via Energy Indicator,Research, 2023, 6: 0118 (IF: 11.036).
  Lei Zheng, Pengfei Liang, Chunshen Long, Haicheng Li, Hanshuang Li, Yuchao Liang, Xiang He, Qilemuge Xi, Yongqiang Xing*, Yongchun Zuo*. EmAtlas: a comprehensive atlas for exploring spatiotemporal activation in mammalian embryogenesis.Nucleic Acids Research, 2023, 51(D1), D924-D932 (IF: 19.160).
  Lei Zheng, Dongyang Liu, Yuan Alex Li, Siqi Yang, Yuchao Liang, Yongqiang Xing*, Yongchun Zuo*.RaacFold: a webserver for 3D visualization and analysis of protein structure by using reduced amino acid alphabets.Nucleic Acids Research, 2022, 50(W1), W633-W638 (IF: 19.160).