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School of Physics Huazhong University of Science and Technology |
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| RESEARCH Interests |
Cryo-EM Tools• EMProt: EMProt improves structure determination from cryo-EM maps Reference: Li T, Chen Ji, Li Hao, Cao Hong, Huang S-Y.* EMProt improves structure determination from cryo-EM maps. Nature Structural & Molecular Biology, 2025. [link] [Software]• CryoEvoBuild: Protein model building for intermediate-resolution cryo-EM maps by integrating evolutionary and experimental information Reference: Chen Ji, Li T, He Jiahua*, Huang S-Y.* Protein model building for intermediate-resolution cryo-EM maps by integrating evolutionary and experimental information. Structure, 2025;S0969-2126(25)00438-1. [link] [Software]• EMInfo: Deciphering Protein Secondary Structures and Nucleic Acids in Cryo-EM Maps Using Deep Learning Reference: Cao Hong, He Jiahua, Li Tao, Huang S-Y.* Deciphering Protein Secondary Structures and Nucleic Acids in Cryo-EM Maps Using Deep Learning. Journal of Chemical Information and Modeling, 2025;65:1641-1652. [link] [Software]• EM2NA: Automated detection and de novo structure modeling of nucleic acids from cryo-EM maps Reference: Li T, Cao Hong, He Jiahua, Huang S-Y.* Automated detection and de novo structure modeling of nucleic acids from cryo-EM maps. Nature Communications, 2024;15:9367. [link] [Software]• EMRNA: All-atom structure determination from cryo-EM maps Reference: Li T, He Jiahua, Cao Hong, Zhang Yi, Chen Ji, Xiao Yi, Huang S-Y.* All-atom RNA structure determination from cryo-EM maps. Nature Biotechnology, 2025;43:97-105. [link] [Software]• EMReady: Improving the quality and interpretability of cryo-EM maps by local and non-local deep learning Reference: He J, Li T, Huang S-Y.* Improvement of cryo-EM maps by simultaneous local and non-local deep learning. Nature Communications, 2023;14:3217. [link] [Software]• EMBuild: Automated model building of protein complexes from intermediate-resolution cryo-EM maps with deep learning-guided assembly Reference: He J, Lin P, Chen J, Cao H, Huang S-Y.* Model building of protein complexes from intermediate-resolution cryo-EM maps with deep learning-guided automatic assembly. Nature Communications, 2022;13:4066. [link] [Software]• DeepMM: Full-length de novo protein structure determination from cryo-EM maps Reference: He J, Huang S-Y.,* Full-length de novo protein structure determination from cryo-EM maps using deep learning. Bioinformatics, 2021;37(20):3480–3490. [link] [Software]• EMNUSS: Protein secondary structure detection in intermediate-resolution cryo-EM maps Reference: He J, Huang S-Y.* EMNUSS: a deep learning framework for secondary structure annotation in cryo-EM maps. Briefings in Bioinformatics, 2021;22(6):bbab156. [link] [Software] |