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Ivan Anishchenko

Showing results (11-20 of 41) with videos related to

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Proceedings of the National Academy of Sciences of the United States of America|January 4, 2020
Improved protein structure prediction using predicted interresidue orientationsJianyi Yang, Ivan Anishchenko, Hahnbeom Park, et al.
Nature Methods|November 23, 2023
Accurate prediction of protein-nucleic acid complexes using RoseTTAFoldNAMinkyung Baek, Ryan McHugh, Ivan Anishchenko, et al.
Nature Communications|February 27, 2021
Improved protein structure refinement guided by deep learning based accuracy estimationNaozumi Hiranuma, Hahnbeom Park, Minkyung Baek, et al.
Proteins|December 7, 2018
Gene ontology improves template selection in comparative protein dockingAnna Hadarovich, Ivan Anishchenko, Alexander V Tuzikov, et al.
Proteins|July 21, 2019
High-accuracy refinement using Rosetta in CASP13Hahnbeom Park, Gyu Rie Lee, David E Kim, et al.
Briefings in Bioinformatics|May 31, 2022
Characterizing and explaining the impact of disease-associated mutations in proteins without known structures or structural homologsNeeladri Sen, Ivan Anishchenko, Nicola Bordin, et al.
Nature Methods|March 29, 2025
Atomic context-conditioned protein sequence design using LigandMPNNJustas Dauparas, Gyu Rie Lee, Robert Pecoraro, et al.
Proteins|September 15, 2017
Modeling CAPRI targets 110-120 by template-based and free docking using contact potential and combined scoring functionPetras J Kundrotas, Ivan Anishchenko, Varsha D Badal, et al.
Iucrj|September 17, 2020
Deep learning enables the atomic structure determination of the Fanconi Anemia core complex from cryoEMDaniel P Farrell, Ivan Anishchenko, Shabih Shakeel, et al.
Protein Science : a Publication of the Protein Society|September 12, 2017
Dockground: A comprehensive data resource for modeling of protein complexesPetras J Kundrotas, Ivan Anishchenko, Taras Dauzhenka, et al.
Pageof 5

Showing results (11-20 of 41) with videos related to

Sort By:
Pageof 5
Proceedings of the National Academy of Sciences of the United States of America|January 4, 2020
Improved protein structure prediction using predicted interresidue orientationsJianyi Yang, Ivan Anishchenko, Hahnbeom Park, et al.
Nature Methods|November 23, 2023
Accurate prediction of protein-nucleic acid complexes using RoseTTAFoldNAMinkyung Baek, Ryan McHugh, Ivan Anishchenko, et al.
Nature Communications|February 27, 2021
Improved protein structure refinement guided by deep learning based accuracy estimationNaozumi Hiranuma, Hahnbeom Park, Minkyung Baek, et al.
Proteins|December 7, 2018
Gene ontology improves template selection in comparative protein dockingAnna Hadarovich, Ivan Anishchenko, Alexander V Tuzikov, et al.
Proteins|July 21, 2019
High-accuracy refinement using Rosetta in CASP13Hahnbeom Park, Gyu Rie Lee, David E Kim, et al.
Briefings in Bioinformatics|May 31, 2022
Characterizing and explaining the impact of disease-associated mutations in proteins without known structures or structural homologsNeeladri Sen, Ivan Anishchenko, Nicola Bordin, et al.
Nature Methods|March 29, 2025
Atomic context-conditioned protein sequence design using LigandMPNNJustas Dauparas, Gyu Rie Lee, Robert Pecoraro, et al.
Proteins|September 15, 2017
Modeling CAPRI targets 110-120 by template-based and free docking using contact potential and combined scoring functionPetras J Kundrotas, Ivan Anishchenko, Varsha D Badal, et al.
Iucrj|September 17, 2020
Deep learning enables the atomic structure determination of the Fanconi Anemia core complex from cryoEMDaniel P Farrell, Ivan Anishchenko, Shabih Shakeel, et al.
Protein Science : a Publication of the Protein Society|September 12, 2017
Dockground: A comprehensive data resource for modeling of protein complexesPetras J Kundrotas, Ivan Anishchenko, Taras Dauzhenka, et al.
Pageof 5