Naozumi Hiranuma, Hahnbeom Park, Minkyung Baek, Ivan Anishchenko, Justas Dauparas, David Baker. Nat Commun 2021
Times Cited: 44
Times Cited: 44
Times Cited
Times Co-cited
Similarity
Improved protein structure prediction using predicted interresidue orientations.
Jianyi Yang, Ivan Anishchenko, Hahnbeom Park, Zhenling Peng, Sergey Ovchinnikov, David Baker. Proc Natl Acad Sci U S A 2020
Jianyi Yang, Ivan Anishchenko, Hahnbeom Park, Zhenling Peng, Sergey Ovchinnikov, David Baker. Proc Natl Acad Sci U S A 2020
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Improved protein structure prediction using potentials from deep learning.
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Highly accurate protein structure prediction with AlphaFold.
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lDDT: a local superposition-free score for comparing protein structures and models using distance difference tests.
Valerio Mariani, Marco Biasini, Alessandro Barbato, Torsten Schwede. Bioinformatics 2013
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Accurate prediction of protein structures and interactions using a three-track neural network.
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Distance-based protein folding powered by deep learning.
Jinbo Xu. Proc Natl Acad Sci U S A 2019
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Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model.
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Jonghun Won, Minkyung Baek, Bohdan Monastyrskyy, Andriy Kryshtafovych, Chaok Seok. Proteins 2019
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HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment.
Michael Remmert, Andreas Biegert, Andreas Hauser, Johannes Söding. Nat Methods 2011
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Critical assessment of methods of protein structure prediction (CASP)-Round XIII.
Andriy Kryshtafovych, Torsten Schwede, Maya Topf, Krzysztof Fidelis, John Moult. Proteins 2019
Andriy Kryshtafovych, Torsten Schwede, Maya Topf, Krzysztof Fidelis, John Moult. Proteins 2019
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QDeep: distance-based protein model quality estimation by residue-level ensemble error classifications using stacked deep residual neural networks.
Md Hossain Shuvo, Sutanu Bhattacharya, Debswapna Bhattacharya. Bioinformatics 2020
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HH-suite3 for fast remote homology detection and deep protein annotation.
Martin Steinegger, Markus Meier, Milot Mirdita, Harald Vöhringer, Stephan J Haunsberger, Johannes Söding. BMC Bioinformatics 2019
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The Protein Data Bank.
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TM-align: a protein structure alignment algorithm based on the TM-score.
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15
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Protein model quality assessment using 3D oriented convolutional neural networks.
Guillaume Pagès, Benoit Charmettant, Sergei Grudinin. Bioinformatics 2019
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24
Smooth orientation-dependent scoring function for coarse-grained protein quality assessment.
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19
Driven to near-experimental accuracy by refinement via molecular dynamics simulations.
Lim Heo, Collin F Arbour, Michael Feig. Proteins 2019
Lim Heo, Collin F Arbour, Michael Feig. Proteins 2019
28
QAcon: single model quality assessment using protein structural and contact information with machine learning techniques.
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Renzhi Cao, Badri Adhikari, Debswapna Bhattacharya, Miao Sun, Jie Hou, Jianlin Cheng. Bioinformatics 2017
13
Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints.
Joe G Greener, Shaun M Kandathil, David T Jones. Nat Commun 2019
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13
Estimation of model accuracy in CASP13.
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19
Evaluation of model refinement in CASP13.
Randy J Read, Massimo D Sammito, Andriy Kryshtafovych, Tristan I Croll. Proteins 2019
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28
The I-TASSER Suite: protein structure and function prediction.
Jianyi Yang, Renxiang Yan, Ambrish Roy, Dong Xu, Jonathan Poisson, Yang Zhang. Nat Methods 2015
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13
Improved protein structure prediction by deep learning irrespective of co-evolution information.
Jinbo Xu, Matthew Mcpartlon, Jin Li. Nat Mach Intell 2021
Jinbo Xu, Matthew Mcpartlon, Jin Li. Nat Mach Intell 2021
15
Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences.
Alexander Rives, Joshua Meier, Tom Sercu, Siddharth Goyal, Zeming Lin, Jason Liu, Demi Guo, Myle Ott, C Lawrence Zitnick, Jerry Ma,[...]. Proc Natl Acad Sci U S A 2021
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13
GraphQA: protein model quality assessment using graph convolutional networks.
Federico Baldassarre, David Menéndez Hurtado, Arne Elofsson, Hossein Azizpour. Bioinformatics 2021
Federico Baldassarre, David Menéndez Hurtado, Arne Elofsson, Hossein Azizpour. Bioinformatics 2021
42
Highly accurate protein structure prediction for the human proteome.
Kathryn Tunyasuvunakool, Jonas Adler, Zachary Wu, Tim Green, Michal Zielinski, Augustin Žídek, Alex Bridgland, Andrew Cowie, Clemens Meyer, Agata Laydon,[...]. Nature 2021
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13
VoroCNN: Deep convolutional neural network built on 3D Voronoi tessellation of protein structures.
Ilia Igashov, Liment Olechnovič, Maria Kadukova, Česlovas Venclovas, Sergei Grudinin. Bioinformatics 2021
Ilia Igashov, Liment Olechnovič, Maria Kadukova, Česlovas Venclovas, Sergei Grudinin. Bioinformatics 2021
71
High-accuracy refinement using Rosetta in CASP13.
Hahnbeom Park, Gyu Rie Lee, David E Kim, Ivan Anishchenko, Qian Cong, David Baker. Proteins 2019
Hahnbeom Park, Gyu Rie Lee, David E Kim, Ivan Anishchenko, Qian Cong, David Baker. Proteins 2019
25
VoroMQA: Assessment of protein structure quality using interatomic contact areas.
Kliment Olechnovič, Česlovas Venclovas. Proteins 2017
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11
Assessment of model accuracy estimations in CASP12.
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Andriy Kryshtafovych, Bohdan Monastyrskyy, Krzysztof Fidelis, Torsten Schwede, Anna Tramontano. Proteins 2018
14
GalaxyRefine2: simultaneous refinement of inaccurate local regions and overall protein structure.
Gyu Rie Lee, Jonghun Won, Lim Heo, Chaok Seok. Nucleic Acids Res 2019
Gyu Rie Lee, Jonghun Won, Lim Heo, Chaok Seok. Nucleic Acids Res 2019
20
11
Distance-scaled, finite ideal-gas reference state improves structure-derived potentials of mean force for structure selection and stability prediction.
Hongyi Zhou, Yaoqi Zhou. Protein Sci 2002
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11
DeepDist: real-value inter-residue distance prediction with deep residual convolutional network.
Tianqi Wu, Zhiye Guo, Jie Hou, Jianlin Cheng. BMC Bioinformatics 2021
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Protein structure prediction using Rosetta.
Carol A Rohl, Charlie E M Strauss, Kira M S Misura, David Baker. Methods Enzymol 2004
Carol A Rohl, Charlie E M Strauss, Kira M S Misura, David Baker. Methods Enzymol 2004
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High-resolution comparative modeling with RosettaCM.
Yifan Song, Frank DiMaio, Ray Yu-Ruei Wang, David Kim, Chris Miles, Tj Brunette, James Thompson, David Baker. Structure 2013
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Relaxation of backbone bond geometry improves protein energy landscape modeling.
Patrick Conway, Michael D Tyka, Frank DiMaio, David E Konerding, David Baker. Protein Sci 2014
Patrick Conway, Michael D Tyka, Frank DiMaio, David E Konerding, David Baker. Protein Sci 2014
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'It will change everything': DeepMind's AI makes gigantic leap in solving protein structures.
Ewen Callaway. Nature 2020
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ModFOLD6: an accurate web server for the global and local quality estimation of 3D protein models.
Ali H A Maghrabi, Liam J McGuffin. Nucleic Acids Res 2017
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9
Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features.
W Kabsch, C Sander. Biopolymers 1983
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GalaxyRefine: Protein structure refinement driven by side-chain repacking.
Lim Heo, Hahnbeom Park, Chaok Seok. Nucleic Acids Res 2013
Lim Heo, Hahnbeom Park, Chaok Seok. Nucleic Acids Res 2013
9
Co-cited is the co-citation frequency, indicating how many articles cite the article together with the query article. Similarity is the co-citation as percentage of the times cited of the query article or the article in the search results, whichever is the lowest. These numbers are calculated for the last 100 citations when articles are cited more than 100 times.