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School of Physics Huazhong University of Science and Technology |
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| RESEARCH Interests |
Cryo-EM Tools• 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] |