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The ability to accurately model the fitness landscape of protein sequences is critical to a wide range of applications, from quantifying the effects of human variants on disease likelihood, to predicting immune-escape mutations in viruses and designing novel biotherapeutic proteins.
Evaluating protein transfer learning with TAPE
Rao, R., Bhattacharya, N., Thomas, N., Duan, Y., Chen, X., Canny, J. F., Abbeel, P., and Song, Y. S · 1906
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Clustal w: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice
Thompson, J. D., Higgins, D. G., and Gibson, T. J · 1994
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Long short-term memory
Hochreiter, S. and Schmidhuber, J · 1997
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The clustal_x windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools
Thompson, J. D., Gibson, T. J., Plewniak, F., Jeanmougin, F., and Higgins, D. G · 1997
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Accurate Measurement of the Effects of All Amino-Acid Mutations on Influenza Hemagglutinin
Doud, M. and Bloom, J · 1999
Earlier work this paper cites.
Predicting deleterious amino acid substitutions
Ng, P. C. and Henikoff, S · 2001
Earlier work this paper cites.
Human non-synonymous snps: server and survey
Ramensky, V., Bork, P., and Sunyaev, S · 2002
Earlier work this paper cites.
Muscle: multiple sequence alignment with high accuracy and high throughput
Edgar, R. C · 2004
Earlier work this paper cites.
Protein flexibility and intrinsic disorder
Radivojac, P., Obradovic, Z., Smith, D. K., Zhu, G., Vucetic, S., Brown, C. J., Lawson, J. D., and Dunker, A. K · 2004
Earlier work this paper cites.
Speech and language processing, 2nd edition
Jurafsky, D. and Martin, J. H · 2008
Earlier work this paper cites.
The probabilistic relevance framework: Bm25 and beyond
Robertson, S. E. and Zaragoza, H · 2009
Earlier work this paper cites.
Protein Model Discrimination Using Mutational Sensitivity Derived from Deep Sequencing
Adkar, B., Tripathi, A., Sahoo, A., Bajaj, K., Goswami, D., Chakrabarti, P., Swarnkar, M., Gokhale, R., and Varadarajan, R · 2011
Earlier work this paper cites.
Accelerated profile hmm searches
Eddy, S. R · 2011
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Predicting the functional impact of protein mutations: application to cancer genomics
Reva, B., Antipin, Y., and Sander, C · 2011
Earlier work this paper cites.
Fast, scalable generation of high-quality protein multiple sequence alignments using clustal omega
Sievers, F., Wilm, A., Dineen, D., Gibson, T. J., Karplus, K., Li, W., Lopez, R., McWilliam, H., Remmert, M., Söding, J., Thompson, J. D., and Higgins, D. G · 2011
Earlier work this paper cites.
A fundamental protein property, thermodynamic stability, revealed solely from large-scale measurements of protein function
Araya, C. L., Fowler, D. M., Chen, W., Muniez, I., Kelly, J. W., and Fields, S · 2012
Earlier work this paper cites.
Deep Sequencing of Systematic Combinatorial Libraries Reveals β \beta -Lactamase Sequence Constraints at High Resolution
Deng, Z., Huang, W., Bakkalbasi, E., Brown, N. G., Adamski, C. J., Rice, K., Muzny, D., Gibbs, R. A., and Palzkill, T · 2012
Earlier work this paper cites.
The spatial architecture of protein function and adaptation
McLaughlin Jr, R. N., Poelwijk, F. J., Raman, A., Gosal, W. S., and Ranganathan, R · 2012
Earlier work this paper cites.
Hhblits: lightning-fast iterative protein sequence searching by hmm-hmm alignment
Remmert, M., Biegert, A., Hauser, A., and Söding, J · 2012
Earlier work this paper cites.
Capturing the mutational landscape of the beta-lactamase TEM-1
Jacquier, H., Birgy, A., Le Nagard, H., Mechulam, Y., Schmitt, E., Glodt, J., Bercot, B., Petit, E., Poulain, J., Barnaud, G., Gros, P.-A., and Tenaillon, O · 2013
Earlier work this paper cites.
Deep mutational scanning of an RRM domain of the Saccharomyces cerevisiae
Melamed, D., Young, D. L., Gamble, C. E., Miller, C. R., and Fields, S · 2013
Earlier work this paper cites.
Analyses of the Effects of All Ubiquitin Point Mutants on Yeast Growth Rate
Roscoe, B. P., Thayer, K. M., Zeldovich, K. B., Fushman, D., and Bolon, D. N · 2013
Earlier work this paper cites.
Activity-enhancing mutations in an E3 ubiquitin ligase identified by high-throughput mutagenesis
Starita, L. M., Pruneda, J. N., Lo, R. S., Fowler, D. M., Kim, H. J., Hiatt, J. B., Shendure, J., Brzovic, P. S., Fields, S., and Klevit, R. E · 2013
Earlier work this paper cites.
A Comprehensive, High-Resolution Map of a Gene’s Fitness Landscape
Firnberg, E., Labonte, J. W., Gray, J. J., and Ostermeier, M · 2014
Earlier work this paper cites.
Deep mutational scanning: a new style of protein science
Fowler, D. M. and Fields, S · 2014
Earlier work this paper cites.
Sequence co-evolution gives 3d contacts and structures of protein complexes
Hopf, T. A., Schärfe, C. P., Rodrigues, J. P., Green, A. G., Kohlbacher, O., Sander, C., Bonvin, A. M., and Marks, D. S · 2014
Earlier work this paper cites.
Comprehensive mutational scanning of a kinase in vivo
Melnikov, A., Rogov, P., Wang, L., Gnirke, A., and Mikkelsen, T. S · 2014
Earlier work this paper cites.
A Comprehensive Biophysical Description of Pairwise Epistasis throughout an Entire Protein Domain
Olson, C., Wu, N., and Sun, R · 2014
Earlier work this paper cites.
A Quantitative High-Resolution Genetic Profile Rapidly Identifies Sequence Determinants of Hepatitis C Viral Fitness and Drug Sensitivity
Qi, H., Olson, C. A., Wu, N. C., Ke, R., Loverdo, C., Chu, V., Truong, S., Remenyi, R., Chen, Z., Du, Y., Su, S.-Y., Al-Mawsawi, L. Q., Wu, T.-T., Chen, S.-H., Lin, C.-Y., Zhong, W., Lloyd-Smith, J. O., and Sun, R · 2014
Earlier work this paper cites.
Systematic Exploration of Ubiquitin Sequence, E1 Activation Efficiency, and Experimental Fitness in Yeast
Roscoe, B. P. and Bolon, D. N · 2014
Earlier work this paper cites.
UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches
Suzek, B. E., Wang, Y., Huang, H., McGarvey, P. B., Wu, C. H., and the UniProt Consortium · 2014
Earlier work this paper cites.
Going deeper with convolutions, 2014
Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., and Rabinovich, A · 2014
Earlier work this paper cites.
Evolving New Protein-Protein Interaction Specificity through Promiscuous Intermediates
Aakre, C., Herrou, J., Phung, T., Perchuk, B., Crosson, S., and Laub, M · 2015
Earlier work this paper cites.
Site-Specific Amino Acid Preferences Are Mostly Conserved in Two Closely Related Protein Homologs
Doud, M. B., Ashenberg, O., and Bloom, J. D · 2015
Earlier work this paper cites.
Massively parallel single-amino-acid mutagenesis
Kitzman, J. O., Starita, L. M., Lo, R. S., Fields, S., and Shendure, J · 2015
Earlier work this paper cites.
Comprehensive Sequence-Flux Mapping of a Levoglucosan Utilization Pathway in E. coli
Klesmith, J. R., Bacik, J.-P., Michalczyk, R., and Whitehead, T. A · 2015
Earlier work this paper cites.
Systematic Mapping of Protein Mutational Space by Prolonged Drift Reveals the Deleterious Effects of Seemingly Neutral Mutations
Rockah-Shmuel, L., Tóth-Petróczy, A., and Tawfik, D. S · 2015
Earlier work this paper cites.
Dissecting enzyme function with microfluidic-based deep mutational scanning
Romero, P. A., Tran, T. M., and Abate, A. R · 2015
Earlier work this paper cites.
Evolvability as a Function of Purifying Selection in TEM-1 β \beta -Lactamase
Stiffler, M., Hekstra, D., and Ranganathan, R · 2015
Earlier work this paper cites.
Functional Constraint Profiling of a Viral Protein Reveals Discordance of Evolutionary Conservation and Functionality
Wu, N. C., Olson, C. A., Du, Y., Le, S., Tran, K., Remenyi, R., Gong, D., Al-Mawsawi, L. Q., Qi, H., Wu, T.-T., and Sun, R · 2015
Earlier work this paper cites.
Quantifying and understanding the fitness effects of protein mutations: Laboratory versus nature
Boucher, J. I., Bolon, D. N., and Tawfik, D. S · 2016
Earlier work this paper cites.
Phenotypic Characterization of a Comprehensive Set of MAPK1 /ERK2 Missense Mutants
Brenan, L., Andreev, A., Cohen, O., Pantel, S., Kamburov, A., Cacchiarelli, D., Persky, N., Zhu, C., Bagul, M., Goetz, E., Burgin, A., Garraway, L., Getz, G., Mikkelsen, T., Piccioni, F., Root, D., and Johannessen, C · 2016
Earlier work this paper cites.
Saturation mutagenesis of the hiv-1 envelope cd4 binding loop reveals residues controlling distinct trimer conformations
Duenas-Decamp, M., Jiang, L., Bolon, D., and Clapham, P. R · 2016
Earlier work this paper cites.
Functional Segregation of Overlapping Genes in HIV
Fernandes, J. D., Faust, T. B., Strauli, N. B., Smith, C., Crosby, D. C., Nakamura, R. L., Hernandez, R. D., and Frankel, A. D · 2016
Earlier work this paper cites.
Experimental Estimation of the Effects of All Amino-Acid Mutations to HIV’s Envelope Protein on Viral Replication in Cell Culture
Haddox, H. K., Dingens, A. S., and Bloom, J. D · 2016
Earlier work this paper cites.
A balance between inhibitor binding and substrate processing confers influenza drug resistance
Jiang, L., Liu, P., Bank, C., Renzette, N., Prachanronarong, K., Yilmaz, L. S., Caffrey, D. R., Zeldovich, K. B., Schiffer, C. A., Kowalik, T. F., et al · 2016
Cited alongside, same era.
RNA Structural Determinants of Optimal Codons Revealed by MAGE-Seq
Kelsic, E. D., Chung, H., Cohen, N., Park, J., Wang, H. H., and Kishony, R · 2016
Cited alongside, same era.
Systematic Mutant Analyses Elucidate General and Client-Specific Aspects of Hsp90 Function
Mishra, P., Flynn, J., Starr, T., and Bolon, D · 2016
Cited alongside, same era.
Local fitness landscape of the green fluorescent protein
Sarkisyan, K. S., Bolotin, D. A., Meer, M. V., Usmanova, D. R., Mishin, A. S., Sharonov, G. V., Ivankov, D. N., Bozhanova, N. G., Baranov, M. S., Soylemez, O., et al · 2016
Cited alongside, same era.
Structured states of disordered proteins from genomic sequences
Toth-Petroczy, A., Palmedo, P., Ingraham, J., Hopf, T. A., Berger, B., Sander, C., and Marks, D. S · 2016
Cited alongside, same era.
High-throughput discovery of trafficking-deficient variants in the cardiac potassium channel KV11.1
Kozek, K. A., Glazer, A. M., Ng, C.-A., Blackwell, D., Egly, C. L., Vanags, L. R., Blair, M., Mitchell, D., Matreyek, K. A., Fowler, D. M., Knollmann, B. C., Vandenberg, J. I., Roden, D. M., and Kroncke, B. M · 2020
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Retrieval-augmented generation for knowledge-intensive nlp tasks
Lewis, P., Perez, E., Piktus, A., Petroni, F., Karpukhin, V., Goyal, N., Kuttler, H., Lewis, M., tau Yih, W., Rocktäschel, T., Riedel, S., and Kiela, D · 2020
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Progen: Language modeling for protein generation, 2020
Madani, A., McCann, B., Naik, N., Keskar, N. S., Anand, N., Eguchi, R. R., Huang, P.-S., and Socher, R · 2020
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Mgnify: the microbiome analysis resource in 2020
Mitchell, A. L., Almeida, A., Beracochea, M., Boland, M. A., Burgin, J., Cochrane, G., Crusoe, M. R., Kale, V., Potter, S. C., Richardson, L. J., Sakharova, E. A., Scheremetjew, M., Korobeynikov, A. I., Shlemov, A., Kunyavskaya, O., Lapidus, A. L., and Finn, R. D · 2020
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Molecular Determinants of Mutant Phenotypes, Inferred from Saturation Mutagenesis Data
Tripathi, A., Gupta, K., Khare, S., Jain, P. C., Patel, S., Kumar, P., Pulianmackal, A. J., Aghera, N., and Varadarajan, R · 2016
Cited alongside, same era.
Unbounded cache model for online language modeling with open vocabulary
Grave, E., Cissé, M., and Joulin, A · 2017
Cited alongside, same era.
Mutation effects predicted from sequence co-variation
Hopf, T. A., Ingraham, J. B., Poelwijk, F. J., Schärfe, C. P., Springer, M., Sander, C., and Marks, D. S · 2017
Cited alongside, same era.
Attention is all you need, 2017
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., and Polosukhin, I · 2017
Cited alongside, same era.
A framework for exhaustively mapping functional missense variants
Weile, J., Sun, S., Cote, A. G., Knapp, J., Verby, M., Mellor, J. C., Wu, Y., Pons, C., Wong, C., Lieshout, N., Yang, F., Tasan, M., Tan, G., Yang, S., Fowler, D. M., Nussbaum, R., Bloom, J. D., Vidal, M., Hill, D. E., Aloy, P., and Roth, F. P · 2017
Cited alongside, same era.
Differential strengths of molecular determinants guide environment specific mutational fates
Dandage, R., Pandey, R., Jayaraj, G., Rai, M., Berger, D., and Chakraborty, K · 2018
Cited alongside, same era.
Accurate classification of BRCA1 variants with saturation genome editing
Findlay, G. M., Daza, R. M., Martin, B., Zhang, M. D., Leith, A. P., Gasperini, M., Janizek, J. D., Huang, X., Starita, L. M., and Shendure, J · 2018
Cited alongside, same era.
Nambiar, A., Heflin, M., Liu, S., Maslov, S., Hopkins, M., and Ritz, A · 2020
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Robust Sequence Determinants of α \alpha -Synuclein Toxicity in Yeast Implicate Membrane Binding
Newberry, R. W., Arhar, T., Costello, J., Hartoularos, G. C., Maxwell, A. M., Naing, Z. Z. C., Pittman, M., Reddy, N. R., Schwarz, D. M. C., Wassarman, D. R., Wu, T. S., Barrero, D., Caggiano, C., Catching, A., Cavazos, T. B., Estes, L. S., Faust, B., Fink, E. A., Goldman, M. A., Gomez, Y. K., Gordon, M. G., Gunsalus, L. M., Hoppe, N., Jaime-Garza, M., Johnson, M. C., Jones, M. G., Kung, A. F., Lopez, K. E., Lumpe, J., Martyn, C., McCarthy, E. E., Miller-Vedam, L. E., Navarro, E. J., Palar, A., Pellegrino, J., Saylor, W., Stephens, C. A., Strickland, J., Torosyan, H., Wankowicz, S. A., Wong, D. R., Wong, G., Redding, S., Chow, E. D., DeGrado, W. F., and Kampmann, M · 2020
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Systematically Scrutinizing the Impact of Substitution Sites on Thermostability and Detergent Tolerance for Bacillus subtilis
Nutschel, C., Fulton, A., Zimmermann, O., Schwaneberg, U., Jaeger, K.-E., and Gohlke, H · 2020
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Transformer protein language models are unsupervised structure learners
Rao, R., Meier, J., Sercu, T., Ovchinnikov, S., and Rives, A · 2020
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An evolution-based model for designing chorismate mutase enzymes
Russ, W. P., Figliuzzi, M., Stocker, C., Barrat-Charlaix, P., Socolich, M., Kast, P., Hilvert, D., Monasson, R., Cocco, S., Weigt, M., et al · 2020
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Deep Mutational Scanning of SARS-CoV-2 Receptor Binding Domain Reveals Constraints on Folding and ACE2 Binding
Starr, T. N., Greaney, A. J., Hilton, S. K., Ellis, D., Crawford, K. H., Dingens, A. S., Navarro, M. J., Bowen, J. E., Tortorici, M. A., Walls, A. C., King, N. P., Veesler, D., and Bloom, J. D · 2020
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Massively parallel variant characterization identifies NUDT15
Suiter, C. C., Moriyama, T., Matreyek, K. A., Yang, W., Scaletti, E. R., Nishii, R., Yang, W., Hoshitsuki, K., Singh, M., Trehan, A., Parish, C., Smith, C., Li, L., Bhojwani, D., Yuen, L. Y. P., Li, C.-k., Li, C.-h., Yang, Y.-l., Walker, G. J., Goodhand, J. R., Kennedy, N. A., Klussmann, F. A., Bhatia, S., Relling, M. V., Kato, M., Hori, H., Bhatia, P., Ahmad, T., Yeoh, A. E. J., Stenmark, P., Fowler, D. M., and Yang, J. J · 2020
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Massively parallel characterization of CYP2C9 variant enzyme activity and abundance
Amorosi, C. J., Chiasson, M. A., McDonald, M. G., Wong, L. H., Sitko, K. A., Boyle, G., Kowalski, J. P., Rettie, A. E., Fowler, D. M., and Dunham, M. J · 2021
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Accurate prediction of protein structures and interactions using a 3-track neural network
Baek, M., Dimaio, F., Anishchenko, I. V., Dauparas, J., Ovchinnikov, S., Lee, G. R., Wang, J., Cong, Q., Kinch, L. N., Schaeffer, R. D., Millán, C., Park, H., Adams, C., Glassman, C. R., DeGiovanni, A. M., Pereira, J. H., Rodrigues, A. V., van Dijk, A. A., Ebrecht, A. C., Opperman, D. J., Sagmeister, T., Buhlheller, C., Pavkov-Keller, T., Rathinaswamy, M. K., Dalwadi, U., Yip, C. K., Burke, J. E., Garcia, K. C., Grishin, N. V., Adams, P. D., Read, R. J., and Baker, D · 2021
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Low-n protein engineering with data-efficient deep learning
Biswas, S., Khimulya, G., Alley, E. C., Esvelt, K. M., and Church, G. M · 2021
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Improving language models by retrieving from trillions of tokens
Borgeaud, S., Mensch, A., Hoffmann, J., Cai, T., Rutherford, E., Millican, K., van den Driessche, G., Lespiau, J.-B., Damoc, B., Clark, A., de Las Casas, D., Guy, A., Menick, J., Ring, R., Hennigan, T. W., Huang, S., Maggiore, L., Jones, C., Cassirer, A., Brock, A., Paganini, M., Irving, G., Vinyals, O., Osindero, S., Simonyan, K., Rae, J. W., Elsen, E., and Sifre, L · 2021
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Flip: Benchmark tasks in fitness landscape inference for proteins
Dallago, C., Mou, J., Johnston, K. E., Wittmann, B. J., Bhattacharya, N., Goldman, S., Madani, A., and Yang, K. K · 2021
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Disease variant prediction with deep generative models of evolutionary data
Frazer, J., Notin, P., Dias, M., Gomez, A., Min, J. K., Brock, K. P., Gal, Y., and Marks, D. S · 2021
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Highly accurate protein structure prediction with alphafold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al · 2021
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Integrating thousands of pten variant activity and abundance measurements reveals variant subgroups and new dominant negatives in cancers
Matreyek, K. A., Stephany, J. J., Ahler, E., and Fowler, D. M · 2021
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Language models enable zero-shot prediction of the effects of mutations on protein function
Meier, J., Rao, R., Verkuil, R., Liu, J., Sercu, T., and Rives, A · 2021
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Train short, test long: Attention with linear biases enables input length extrapolation, 2021
Press, O., Smith, N. A., and Lewis, M · 2021
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Msa transformer
Rao, R., Liu, J., Verkuil, R., Meier, J., Canny, J. F., Abbeel, P., Sercu, T., and Rives, A · 2021
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Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences
Rives, A., Meier, J., Sercu, T., Goyal, S., Lin, Z., Liu, J., Guo, D., Ott, M., Zitnick, C. L., Ma, J., et al · 2021
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Protein design and variant prediction using autoregressive generative models
Shin, J.-E., Riesselman, A. J., Kollasch, A. W., McMahon, C., Simon, E., Sander, C., Manglik, A., Kruse, A. C., and Marks, D. S · 2021
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Generative aav capsid diversification by latent interpolation
Sinai, S., Jain, N., Church, G. M., and Kelsic, E. D · 2021
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Primer: Searching for efficient transformers for language modeling, 2021
So, D. R., Mańke, W., Liu, H., Dai, Z., Shazeer, N., and Le, Q. V · 2021
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A structured observation distribution for generative biological sequence prediction and forecasting
Weinstein, E. N. and Marks, D. S · 2021
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Deep Mutagenesis of a Transporter for Uptake of a Non-Native Substrate Identifies Conformationally Dynamic Regions
Young, H. J., Chan, M., Selvam, B., Szymanski, S. K., Shukla, D., and Procko, E · 2021
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Mapping the energetic and allosteric landscapes of protein binding domains
Faure, A. J., Domingo, J., Schmiedel, J. M., Hidalgo-Carcedo, C., Diss, G., and Lehner, B · 2022
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Rita: a study on scaling up generative protein sequence models
Hesslow, D., ed. Zanichelli, N., Notin, P., Poli, I., and Marks, D. S · 2022
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Correlation of fitness landscapes from three orthologous TIM barrels originates from sequence and structure constraints
Chan, Y. H., Venev, S. V., Zeldovich, K. B., and Matthews, C. R · 2041
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Single-mutation fitness landscapes for an enzyme on multiple substrates reveal specificity is globally encoded
Wrenbeck, E. E., Azouz, L. R., and Whitehead, T. A · 2041
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High-throughput profiling of influenza A virus hemagglutinin gene at single-nucleotide resolution
Wu, N. C., Young, A. P., Al-Mawsawi, L. Q., Olson, C. A., Feng, J., Qi, H., Chen, S.-H., Lu, I.-H., Lin, C.-Y., Chin, R. G., Luan, H. H., Nguyen, N., Nelson, S. F., Li, X., Wu, T.-T., and Sun, R · 2045
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Deconstruction of the Ras switching cycle through saturation mutagenesis
Bandaru, P., Shah, N. H., Bhattacharyya, M., Barton, J. P., Kondo, Y., Cofsky, J. C., Gee, C. L., Chakraborty, A. K., Kortemme, T., Ranganathan, R., and Kuriyan, J · 2050
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Comprehensive exploration of the translocation, stability and substrate recognition requirements in VIM-2 lactamase
Chen, J. Z., Fowler, D. M., and Tokuriki, N · 2050
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Multiplexed measurement of variant abundance and activity reveals VKOR topology, active site and human variant impact
Chiasson, M. A., Rollins, N. J., Stephany, J. J., Sitko, K. A., Matreyek, K. A., Verby, M., Sun, S., Roth, F. P., DeSloover, D., Marks, D. S., Rettie, A. E., and Fowler, D. M · 2050
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Comprehensive fitness maps of Hsp90 show widespread environmental dependence
Flynn, J. M., Rossouw, A., Cote-Hammarlof, P., Fragata, I., Mavor, D., Hollins, C., Bank, C., and Bolon, D. N · 2050
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Mapping mutational effects along the evolutionary landscape of HIV envelope
Haddox, H. K., Dingens, A. S., Hilton, S. K., Overbaugh, J., and Bloom, J. D · 2050
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Structural and functional characterization of G protein–coupled receptors with deep mutational scanning
Jones, E. M., Lubock, N. B., Venkatakrishnan, A., Wang, J., Tseng, A. M., Paggi, J. M., Latorraca, N. R., Cancilla, D., Satyadi, M., Davis, J. E., Babu, M. M., Dror, R. O., and Kosuri, S · 2050
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Globally defining the effects of mutations in a picornavirus capsid
Mattenberger, F., Latorre, V., Tirosh, O., Stern, A., and Geller, R · 2050
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Determination of ubiquitin fitness landscapes under different chemical stresses in a classroom setting
Mavor, D., Barlow, K., Thompson, S., Barad, B. A., Bonny, A. R., Cario, C. L., Gaskins, G., Liu, Z., Deming, L., Axen, S. D., Caceres, E., Chen, W., Cuesta, A., Gate, R. E., Green, E. M., Hulce, K. R., Ji, W., Kenner, L. R., Mensa, B., Morinishi, L. S., Moss, S. M., Mravic, M., Muir, R. K., Niekamp, S., Nnadi, C. I., Palovcak, E., Poss, E. M., Ross, T. D., Salcedo, E. C., See, S. K., Subramaniam, M., Wong, A. W., Li, J., Thorn, K. S., Conchúir, S. O., Roscoe, B. P., Chow, E. D., DeRisi, J. L., Kortemme, T., Bolon, D. N., and Fraser, J. S · 2050
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The genetic landscape for amyloid beta fibril nucleation accurately discriminates familial Alzheimer’s disease mutations
Seuma, M., Faure, A. J., Badia, M., Lehner, B., and Bolognesi, B · 2050
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Comprehensive mapping of adaptation of the avian influenza polymerase protein PB2 to humans
Soh, Y. S., Moncla, L. H., Eguia, R., Bedford, T., and Bloom, J. D · 2050
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Altered expression of a quality control protease in E. coli reshapes the in vivo mutational landscape of a model enzyme
Thompson, S., Zhang, Y., Ingle, C., Reynolds, K. A., and Kortemme, T · 2050
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Deep mutational scanning of the Neisseria meningitidis
Kennouche, P., Charles‐Orszag, A., Nishiguchi, D., Goussard, S., Imhaus, A., Dupré, M., Chamot‐Rooke, J., and Duménil, G · 2075
Closest in time.