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Protein language models are a powerful tool for learning protein representations through pre-training on vast protein sequence datasets.
Scop: a structural classification of proteins database for the investigation of sequences and structures
Alexey G Murzin, Steven E Brenner, Tim Hubbard, and Cyrus Chothia · 1995
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An integrated view of protein evolution
Csaba Pál, Balázs Papp, and Martin J Lercher · 2006
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Protein structure databases with new web services for structural biology and biomedical research
Daron M Standley, Akira R Kinjo, Kengo Kinoshita, and Haruki Nakamura · 2008
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A large-scale evaluation of computational protein function prediction
Predrag Radivojac, Wyatt T Clark, Tal Ronnen Oron, Alexandra M Schnoes, Tobias Wittkop, Artem Sokolov, Kiley Graim, Christopher Funk, Karin Verspoor, Asa Ben-Hur, et al · 2013
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A draft map of the human proteome
Min-Sik Kim, Sneha M Pinto, Derese Getnet, Raja Sekhar Nirujogi, Srikanth S Manda, Raghothama Chaerkady, Anil K Madugundu, Dhanashree S Kelkar, Ruth Isserlin, Shobhit Jain, et al · 2014
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Combining evolutionary information extracted from frequency profiles with sequence-based kernels for protein remote homology detection
Bin Liu, Deyuan Zhang, Ruifeng Xu, Jinghao Xu, Xiaolong Wang, Qingcai Chen, Qiwen Dong, and Kuo-Chen Chou · 2014
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Local fitness landscape of the green fluorescent protein
Karen S Sarkisyan, Dmitry A Bolotin, Margarita V Meer, Dinara R Usmanova, Alexander S Mishin, George V Sharonov, Dmitry N Ivankov, Nina G Bozhanova, Mikhail S Baranov, Onuralp Soylemez, et al · 2016
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Adaptation in protein fitness landscapes is facilitated by indirect paths
Nicholas C Wu, Lei Dai, C Anders Olson, James O Lloyd-Smith, and Ren Sun · 2016
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Deeploc: prediction of protein subcellular localization using deep learning
José Juan Almagro Armenteros, Casper Kaae Sønderby, Søren Kaae Sønderby, Henrik Nielsen, and Ole Winther · 2017
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Global analysis of protein folding using massively parallel design, synthesis, and testing
Gabriel J Rocklin et al · 2017
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Learning protein sequence embeddings using information from structure
Tristan Bepler and Bonnie Berger · 2018
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A comprehensive review and comparison of different computational methods for protein remote homology detection
Junjie Chen, Mingyue Guo, Xiaolong Wang, and Bin Liu · 2018
Cited alongside, same era.
Ecpred: a tool for the prediction of the enzymatic functions of protein sequences based on the ec nomenclature
Alperen Dalkiran, Ahmet Sureyya Rifaioglu, Maria Jesus Martin, Rengul Cetin-Atalay, Volkan Atalay, and Tunca Doğan · 2018
Cited alongside, same era.
Quantitative missense variant effect prediction using large-scale mutagenesis data
Vanessa E Gray, Ronald J Hause, Jens Luebeck, Jay Shendure, and Douglas M Fowler · 2018
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Deepsf: deep convolutional neural network for mapping protein sequences to folds
Jie Hou, Badri Adhikari, and Jianlin Cheng · 2018
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Mutant phenotypes for thousands of bacterial genes of unknown function
Morgan N Price, Kelly M Wetmore, R Jordan Waters, Mark Callaghan, Jayashree Ray, Hualan Liu, Jennifer V Kuehl, Ryan A Melnyk, Jacob S Lamson, Yumi Suh, et al · 2018
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Learning from protein structure with geometric vector perceptrons
Bowen Jing, Stephan Eismann, Pratham N. Soni, and Ron O. Dror · 2021
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Msa transformer
Roshan M Rao, Jason Liu, Robert Verkuil, Joshua Meier, John Canny, Pieter Abbeel, Tom Sercu, and Alexander Rives · 2021
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Proteinfer: deep networks for protein functional inference
Theo Sanderson, Maxwell L Bileschi, David Belanger, and Lucy J Colwell · 2021
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Structure-aware protein self-supervised learning
Can (Sam) Chen, Jingbo Zhou, Fan Wang, Xue Liu, and Dejing Dou · 2022
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Tm-vec: template modeling vectors for fast homology detection and alignment
Tymor Hamamsy, James T Morton, Daniel Berenberg, Nicholas Carriero, Vladimir Gligorijevic, Robert Blackwell, Charlie EM Strauss, Julia Koehler Leman, Kyunghyun Cho, and Richard Bonneau · 2022
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PEER: A comprehensive and multi-task benchmark for protein sequence understanding
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Deep learning enables high-quality and high-throughput prediction of enzyme commission numbers
Jae Yong Ryu, Hyun Uk Kim, and Sang Yup Lee · 2019
Cited alongside, same era.
Meltome atlas—thermal proteome stability across the tree of life
Anna Jarzab, Nils Kurzawa, Thomas Hopf, Matthias Moerch, Jana Zecha, Niels Leijten, Yangyang Bian, Eva Musiol, Melanie Maschberger, Gabriele Stoehr, et al · 2020
Cited alongside, same era.
Deep diversification of an aav capsid protein by machine learning
Drew H Bryant, Ali Bashir, Sam Sinai, Nina K Jain, Pierce J Ogden, Patrick F Riley, George M Church, Lucy J Colwell, and Eric D Kelsic · 2021
Cited alongside, same era.
Flip: Benchmark tasks in fitness landscape inference for proteins
Christian Dallago, Jody Mou, Kadina E Johnston, Bruce Wittmann, Nick Bhattacharya, Samuel Goldman, Ali Madani, and Kevin K Yang · 2021
Cited alongside, same era.
Prottrans: Towards cracking the language of lifes code through self-supervised deep learning and high performance computing
Ahmed Elnaggar, Michael Heinzinger, Christian Dallago, Ghalia Rehawi, Wang Yu, Llion Jones, Tom Gibbs, Tamas Feher, Christoph Angerer, Martin Steinegger, Debsindhu Bhowmik, and Burkhard Rost · 2021
Cited alongside, same era.
Structure-based protein function prediction using graph convolutional networks
Vladimir Gligorijević, P Douglas Renfrew, Tomasz Kosciolek, Julia Koehler Leman, Daniel Berenberg, Tommi Vatanen, Chris Chandler, Bryn C Taylor, Ian M Fisk, Hera Vlamakis, et al · 2021
Cited alongside, same era.
Evaluating protein transfer learning with tape
Roshan Rao, Nicholas Bhattacharya, Neil Thomas, Yan Duan, Peter Chen, John Canny, Pieter Abbeel, and Yun Song
Cited in the paper.
Minghao Xu, Zuobai Zhang, Jiarui Lu, Zhaocheng Zhu, Yangtian Zhang, Chang Ma, Runcheng Liu, and Jian Tang · 2022
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Ankh: Optimized protein language model unlocks general-purpose modelling
Ahmed Elnaggar, Hazem Essam, Wafaa Salah-Eldin, Walid Moustafa, Mohamed Elkerdawy, Charlotte Rochereau, and Burkhard Rost · 2023
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Evolutionary-scale prediction of atomic-level protein structure with a language model
Zeming Lin, Halil Akin, Roshan Rao, Brian Hie, Zhongkai Zhu, Wenting Lu, Nikita Smetanin, Robert Verkuil, Ori Kabeli, Yaniv Shmueli, et al · 2023
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Saprot: Protein language modeling with structure-aware vocabulary
Jin Su, Chenchen Han, Yuyang Zhou, Junjie Shan, Xibin Zhou, and Fajie Yuan · 2023
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Enzyme function prediction using contrastive learning
Tianhao Yu, Haiyang Cui, Jianan Canal Li, Yunan Luo, Guangde Jiang, and Huimin Zhao · 2023
Later among the works it cites.