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Protein modeling is an increasingly popular area of machine learning research.
The kinetics of formation of native ribonuclease during oxidation of the reduced polypeptide chain
C B Anfinsen, E Haber, M Sela, F H White, and Jr · 1961
Earlier work this paper cites.
Protein Structure Relationships Revealed by Mutational Analysis
C Yanofsky, V Horn, and D Thorpe · 1964
Earlier work this paper cites.
Identification of common molecular subsequences
Temple F Smith, Michael S Waterman, et al · 1981
Earlier work this paper cites.
Recommendations on nomenclature and symbolism for amino acids and peptides
IUPAC-IUB · 1984
Earlier work this paper cites.
Coordinated amino acid changes in homologous protein families
D Altschuh, T Vernet, P Berti, D Moras, and K Nagai · 1988
Earlier work this paper cites.
Basic local alignment search tool
Stephen F. Altschul, Warren Gish, Webb Miller, Eugene W. Myers, and David J. Lipman · 1990
Earlier work this paper cites.
Proteins: structures and molecular properties
Thomas E Creighton · 1993
Earlier work this paper cites.
Gapped blast and psi-blast: a new generation of protein database search programs
Stephen F Altschul, Thomas L Madden, Alejandro A Schäffer, Jinghui Zhang, Zheng Zhang, Webb Miller, and David J Lipman · 1997
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Profile hidden markov models
Sean R. Eddy · 1998
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Assessing sequence comparison methods with reliable structurally identified distant evolutionary relationships
Steven E Brenner, Cyrus Chothia, and Tim JP Hubbard · 1998
Earlier work this paper cites.
Biological sequence analysis: probabilistic models of proteins and nucleic acids
Richard Durbin, Sean R Eddy, Anders Krogh, and Graeme Mitchison · 1998
Earlier work this paper cites.
Twilight zone of protein sequence alignments
Burkhard Rost · 1999
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Evaluation and improvement of multiple sequence methods for protein secondary structure prediction
James A Cuff and Geoffrey J Barton · 1999
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The protein data bank
Helen M Berman, John Westbrook, Zukang Feng, Gary Gilliland, Talapady N Bhat, Helge Weissig, Ilya N Shindyalov, and Philip E Bourne · 2000
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The cost and value of three-dimensional protein structure
Raymond C Stevens · 2003
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Semi-supervised protein classification using cluster kernels
Jason Weston, Dengyong Zhou, André Elisseeff, William S Noble, and Christina S Leslie · 2004
Earlier work this paper cites.
The HHpred interactive server for protein homology detection and structure prediction
J. Soding, A. Biegert, and A. N. Lupas · 2005
Earlier work this paper cites.
The swiss-model workspace: a web-based environment for protein structure homology modelling
Konstantin Arnold, Lorenza Bordoli, Jürgen Kopp, and Torsten Schwede · 2006
Earlier work this paper cites.
Prediction of protein function from networks
Hyunjung Shin, Koji Tsuda, B Schölkopf, A Zien, et al · 2006
Earlier work this paper cites.
Modular protein engineering in emerging cancer therapies
Esther Vazquez, Neus Ferrer-Miralles, Ramon Mangues, Jose L Corchero, Jr Schwartz, Antonio Villaverde, et al · 2009
Earlier work this paper cites.
Semi-supervised learning
Olivier Chapelle, Bernhard Scholkopf, and Alexander Zien · 2009
Cited alongside, same era.
Recurrent neural network based language model
Tomáš Mikolov, Martin Karafiát, Lukáš Burget, Jan Černockỳ, and Sanjeev Khudanpur · 2010
Cited alongside, same era.
A series of pdb related databases for everyday needs
Robbie P Joosten, Tim AH Te Beek, Elmar Krieger, Maarten L Hekkelman, Rob WW Hooft, Reinhard Schneider, Chris Sander, and Gert Vriend · 2010
Cited alongside, same era.
Optimization of affinity, specificity and function of designed influenza inhibitors using deep sequencing
Timothy A Whitehead, Aaron Chevalier, Yifan Song, Cyrille Dreyfus, Sarel J Fleishman, Cecilia De Mattos, Chris A Myers, Hetunandan Kamisetty, Patrick Blair, Ian A Wilson, et al · 2012
Cited alongside, same era.
HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment
Michael Remmert, Andreas Biegert, Andreas Hauser, and Johannes Söding · 2012
Cited alongside, same era.
UniProt: a worldwide hub of protein knowledge
The UniProt Consortium · 2018
Later among the works it cites.
Deep Contextualized Word Representations
Matthew Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer · 2018
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Critical assessment of methods of protein structure prediction (CASP)-Round XII
John Moult, Krzysztof Fidelis, Andriy Kryshtafovych, Torsten Schwede, and Anna Tramontano · 2018
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Deep generative models of genetic variation capture the effects of mutations
Adam J. Riesselman, John B. Ingraham, and Debora S. Marks · 2018
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Learned protein embeddings for machine learning
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Strategies and molecular tools to fight antimicrobial resistance: resistome, transcriptome, and antimicrobial peptides
Leticia Stephan Tavares, Carolina dos Santos Fernandes da Silva, Vinicius Carius Souza, Vânia Lúcia da Silva, Cláudio Galuppo Diniz, and Marcelo De Oliveira Santos · 2013
Cited alongside, same era.
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
Jeff Donahue, Yangqing Jia, Oriol Vinyals, Judy Hoffman, Ning Zhang, Eric Tzeng, and Trevor Darrell · 2013
Cited alongside, same era.
Scope: Structural classification of proteins—extended, integrating scop and astral data and classification of new structures
Naomi K Fox, Steven E Brenner, and John-Marc Chandonia · 2013
Cited alongside, same era.
One contact for every twelve residues allows robust and accurate topology-level protein structure modeling
David E. Kim, Frank DiMaio, Ray Yu-Ruei Wang, Yifan Song, and David Baker · 2014
Cited alongside, same era.
CCMpred—fast and precise prediction of protein residue–residue contacts from correlated mutations
Stefan Seemayer, Markus Gruber, and Johannes Söding · 2014
Cited alongside, same era.
Unexpected features of the dark proteome
Nelson Perdigão, Julian Heinrich, Christian Stolte, Kenneth S. Sabir, Michael J. Buckley, Bruce Tabor, Beth Signal, Brian S. Gloss, Christopher J. Hammang, Burkhard Rost, Andrea Schafferhans, and Seán I. O’Donoghue · 2015
Cited alongside, same era.
JPred4: a protein secondary structure prediction server
Alexey Drozdetskiy, Christian Cole, James Procter, and Geoffrey J. Barton · 2015
Cited alongside, same era.
Kevin K Yang, Zachary Wu, Claire N Bedbrook, and Frances H Arnold · 2018
Later among the works it cites.
Machine learning in protein engineering
Kevin K Yang, Zachary Wu, and Frances H Arnold · 2018
Later among the works it cites.
Assessment of contact predictions in casp12: Co-evolution and deep learning coming of age
Joerg Schaarschmidt, Bohdan Monastyrskyy, Andriy Kryshtafovych, and Alexandre MJJ Bonvin · 2018
Later among the works it cites.
Critical assessment of methods of protein structure prediction (casp)—round xii
John Moult, Krzysztof Fidelis, Andriy Kryshtafovych, Torsten Schwede, and Anna Tramontano · 2018
Later among the works it cites.
Major new microbial groups expand diversity and alter our understanding of the tree of life
Cindy J Castelle and Jillian F Banfield · 2018
Later among the works it cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever · 2019
Closest in time.
Learning protein sequence embeddings using information from structure
Tristan Bepler and Bonnie Berger · 2019
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Unified rational protein engineering with sequence-only deep representation learning
Ethan C. Alley, Grigory Khimulya, Surojit Biswas, Mohammed AlQuraishi, and George M. Church · 2019
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ProteinNet: a standardized data set for machine learning of protein structure
Mohammed AlQuraishi · 2019
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Modeling the Language of Life - Deep Learning Protein Sequences
Michael Heinzinger, Ahmed Elnaggar, Yu Wang, Christian 4 Dallago, Dmitrii Nachaev, Florian Matthes, and & Burkhard Rost · 2019
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Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences
Alexander Rives, Siddharth Goyal, Joshua Meier, Demi Guo, Myle Ott, C. Lawrence Zitnick, Jerry Ma, and Rob Fergus · 2019
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Superglue: A stickier benchmark for general-purpose language understanding systems
Alex Wang, Yada Pruksachatkun, Nikita Nangia, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R Bowman · 2019
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The Pfam protein families database in 2019
Sara El-Gebali, Jaina Mistry, Alex Bateman, Sean R Eddy, Aurélien Luciani, Simon C Potter, Matloob Qureshi, Lorna J Richardson, Gustavo A Salazar, Alfredo Smart, Erik L L Sonnhammer, Layla Hirsh, Lisanna Paladin, Damiano Piovesan, Silvio C E Tosatto, and Robert D Finn · 2019
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Netsurfp-2.0: Improved prediction of protein structural features by integrated deep learning
Michael Schantz Klausen, Martin Closter Jespersen, Henrik Nielsen, Kamilla Kjaergaard Jensen, Vanessa Isabell Jurtz, Casper Kaae Soenderby, Morten Otto Alexander Sommer, Ole Winther, Morten Nielsen, Bent Petersen, et al · 2019
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Casx enzymes comprise a distinct family of rna-guided genome editors
Jun-Jie Liu, Natalia Orlova, Benjamin L Oakes, Enbo Ma, Hannah B Spinner, Katherine LM Baney, Jonathan Chuck, Dan Tan, Gavin J Knott, Lucas B Harrington, et al · 2019
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