DiffModeler
Wang, X., Zhu, H., Terashi, G., Taluja, M., & Kihara, D. (2023).
DiffModeler: Large Macromolecular Structure Modeling for Cryo-EM Maps Using Diffusion Model.
Nature Methods, accepted (2024),
Early version available at
bioRxiv
DeepMainMast
Terashi, G., Wang, X., Prasad, D. et al. (2023).
DeepMainmast: integrated protocol of protein structure modeling for cryo-EM with deep learning and structure prediction.
Nature Methods, 21: 122-131 (2024),
https://www.nature.com/articles/s41592-023-02099-0
CryoREAD
DAQ Score
Terashi, G., Wang, X., Maddhuri Venkata Subramaniya, S. R., Tesmer, J. J., & Kihara, D. (2022).
Residue-wise local quality estimation for protein models from cryo-EM maps.
Nature Methods,
19(
9),
1116-1125.
https://www.nature.com/articles/s41592-022-01574-4
DAQ-Refine
Terashi, G., Wang, X., Kihara, D. (2023).
Protein model refinement for cryo-EM maps using AlphaFold2 and the DAQ score.
Acta Crystallographica Section D Structural Biology,
79,
10–21.
https://doi.org/10.1107/s2059798322011676
Emap2sec
Maddhuri Venkata Subramaniya, S. R., Terashi, G., & Kihara, D. (2019).
Protein secondary structure detection in intermediate-resolution cryo-EM maps using deep learning.
Nature Methods,
16(9),
911-917.
https://www.nature.com/articles/s41592-019-0500-1
Emap2sec+
Wang, X., Alnabati, E., Aderinwale, T. W., Subramaniya, S. R. M. V., Terashi, G., & Kihara, D. (2021).
Detecting protein and DNA/RNA structures in cryo-EM maps of intermediate resolution using deep learning.
Nature Communications,
12(1),
2302
https://www.nature.com/articles/s41467-021-22577-3
MainMast
VESPER
Han, X., Terashi, G., Christoffer, C., Chen, S., & Kihara, D. (2021).
VESPER: global and local cryo-EM map alignment using local density vectors.
Nature Communications,
12(1),
2090.
https://www.nature.com/articles/s41467-021-22401-y