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Ivan Anishchenko
Ivan Anishchenko
Vilya
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Title
Cited by
Cited by
Year
Accurate prediction of protein structures and interactions using a three-track neural network
M Baek, F DiMaio, I Anishchenko, J Dauparas, S Ovchinnikov, GR Lee, ...
Science 373 (6557), 871-876, 2021
33402021
Improved protein structure prediction using predicted interresidue orientations
J Yang, I Anishchenko, H Park, Z Peng, S Ovchinnikov, D Baker
Proceedings of the National Academy of Sciences 117 (3), 1496-1503, 2020
12582020
Robust deep learning–based protein sequence design using ProteinMPNN
J Dauparas, I Anishchenko, N Bennett, H Bai, RJ Ragotte, LF Milles, ...
Science 378 (6615), 49-56, 2022
5082022
De novo protein design by deep network hallucination
I Anishchenko, SJ Pellock, TM Chidyausiku, TA Ramelot, S Ovchinnikov, ...
Nature 600 (7889), 547-552, 2021
4022021
Computed structures of core eukaryotic protein complexes
IR Humphreys, J Pei, M Baek, A Krishnakumar, I Anishchenko, ...
Science 374 (6573), eabm4805, 2021
3602021
The trRosetta server for fast and accurate protein structure prediction
Z Du, H Su, W Wang, L Ye, H Wei, Z Peng, I Anishchenko, D Baker, ...
Nature protocols 16 (12), 5634-5651, 2021
3482021
Scaffolding protein functional sites using deep learning
J Wang, S Lisanza, D Juergens, D Tischer, JL Watson, KM Castro, ...
Science 377 (6604), 387-394, 2022
2332022
Protein interaction networks revealed by proteome coevolution
Q Cong, I Anishchenko, S Ovchinnikov, D Baker
Science 365 (6449), 185-189, 2019
2302019
Improved protein structure refinement guided by deep learning based accuracy estimation
N Hiranuma, H Park, M Baek, I Anishchenko, J Dauparas, D Baker
Nature communications 12 (1), 1340, 2021
2062021
Origins of coevolution between residues distant in protein 3D structures
I Anishchenko, S Ovchinnikov, H Kamisetty, D Baker
Proceedings of the National Academy of Sciences 114 (34), 9122-9127, 2017
1812017
Prediction of homoprotein and heteroprotein complexes by protein docking and template‐based modeling: a CASP‐CAPRI experiment
MF Lensink, S Velankar, A Kryshtafovych, SY Huang, ...
Proteins: Structure, Function, and Bioinformatics 84, 323-348, 2016
1652016
Protein sequence design by conformational landscape optimization
C Norn, BIM Wicky, D Juergens, S Liu, D Kim, D Tischer, B Koepnick, ...
Proceedings of the National Academy of Sciences 118 (11), e2017228118, 2021
159*2021
De novo design of luciferases using deep learning
AHW Yeh, C Norn, Y Kipnis, D Tischer, SJ Pellock, D Evans, P Ma, ...
Nature 614 (7949), 774-780, 2023
1572023
Protein contact prediction using metagenome sequence data and residual neural networks
Q Wu, Z Peng, I Anishchenko, Q Cong, D Baker, J Yang
Bioinformatics 36 (1), 41-48, 2020
932020
Dockground: a comprehensive data resource for modeling of protein complexes
PJ Kundrotas, I Anishchenko, T Dauzhenka, I Kotthoff, D Mnevets, ...
Protein Science 27 (1), 172-181, 2018
832018
Computational model of the HIV-1 subtype A V3 loop: study on the conformational mobility for structure-based anti-AIDS drug design
AM Andrianov, IV Anishchenko
Journal of Biomolecular Structure and Dynamics 27 (2), 179-193, 2009
522009
ProteinGCN: Protein model quality assessment using graph convolutional networks
S Sanyal, I Anishchenko, A Dagar, D Baker, P Talukdar
BioRxiv, 2020.04. 06.028266, 2020
472020
Protein tertiary structure prediction and refinement using deep learning and Rosetta in CASP14
I Anishchenko, M Baek, H Park, N Hiranuma, DE Kim, J Dauparas, ...
Proteins: Structure, Function, and Bioinformatics 89 (12), 1722-1733, 2021
442021
Design of proteins presenting discontinuous functional sites using deep learning
D Tischer, S Lisanza, J Wang, R Dong, I Anishchenko, LF Milles, ...
Biorxiv, 2020.11. 29.402743, 2020
412020
High‐accuracy refinement using Rosetta in CASP13
H Park, GR Lee, DE Kim, I Anishchenko, Q Cong, D Baker
Proteins: Structure, Function, and Bioinformatics 87 (12), 1276-1282, 2019
412019
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