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We present a multi-objective binder design paradigm based on instruction fine-tuning and direct preference optimization (DPO) of autoregressive protein language models (pLMs).
Rank analysis of incomplete block designs: I. the method of paired comparisons
Ralph Allan Bradley and Milton E Terry · 1952
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Perplexity—a measure of the difficulty of speech recognition tasks
Fred Jelinek, Robert L Mercer, Lalit R Bahl, and James K Baker · 1977
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Pepnn: a deep attention model for the identification of peptide binding sites
Osama Abdin, Satra Nim, Han Wen, and Philip M Kim · 2022
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Protein structure and sequence generation with equivariant denoising diffusion probabilistic models
Namrata Anand and Tudor Achim · 2022
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Constitutional ai: Harmlessness from ai feedback
Yuntao Bai, Saurav Kadavath, Sandipan Kundu, Amanda Askell, Jackson Kernion, Andy Jones, Anna Chen, Anna Goldie, Azalia Mirhoseini, Cameron McKinnon, et al · 2022
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Protgpt2 is a deep unsupervised language model for protein design
Noelia Ferruz, Steffen Schmidt, and Birte Höcker · 2022
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Solubility-aware protein binding peptide design using alphafold
Takatsugu Kosugi and Masahito Ohue · 2022
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Language models of protein sequences at the scale of evolution enable accurate structure prediction
Zeming Lin, Halil Akin, Roshan Rao, Brian Hie, Zhongkai Zhu, Wenting Lu, Allan dos Santos Costa, Maryam Fazel-Zarandi, Tom Sercu, Sal Candido, et al · 2022
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Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
Pairing interacting protein sequences using masked language modeling
Umberto Lupo, Damiano Sgarbossa, and Anne-Florence Bitbol · 2023
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Propedia v2. 3: A novel representation approach for the peptide-protein interaction database using graph-based structural signatures
Pedro Martins, Diego Mariano, Frederico Chaves Carvalho, Luana Luiza Bastos, Lucas Moraes, Vivian Paixão, and Raquel Cardoso de Melo-Minardi · 2023
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Progen2: exploring the boundaries of protein language models
Erik Nijkamp, Jeffrey A Ruffolo, Eli N Weinstein, Nikhil Naik, and Ali Madani · 2023
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Preference optimization for molecular language models
Ryan Park, Ryan Theisen, Navriti Sahni, Marcel Patek, Anna Cichońska, and Rayees Rahman · 2023
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Direct preference optimization: Your language model is secretly a reward model
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bioRxiv [Preprint] , 2023
In silico evolution of protein binders with deep learning models for structure prediction and sequence design · 2023
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Protein generation with evolutionary diffusion: sequence is all you need
Sarah Alamdari, Nitya Thakkar, Rianne van den Berg, Alex Xijie Lu, Nicolo Fusi, Ava Pardis Amini, and Kevin K Yang · 2023
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Peptide binder design with inverse folding and protein structure prediction
Patrick Bryant and Arne Elofsson · 2023
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Pepmlm: Target sequence-conditioned generation of peptide binders via masked language modeling
Tianlai Chen, Sarah Pertsemlidis, Venkata Srikar Kavirayuni, Pranay Vure, Rishab Pulugurta, Ashley Hsu, Sophia Vincoff, Vivian Yudistyra, Lauren Hong, Tian Wang, et al · 2023
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Generative antibody design for complementary chain pairing sequences through encoder-decoder language model
Simon Chu and Kathy Wei · 2023
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Qlora: Efficient finetuning of quantized llms
Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer · 2023
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Protein design with guided discrete diffusion
Nate Gruver, Samuel Stanton, Nathan C Frey, Tim GJ Rudner, Isidro Hotzel, Julien Lafrance-Vanasse, Arvind Rajpal, Kyunghyun Cho, and Andrew Gordon Wilson · 2023
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Rafael Rafailov, Archit Sharma, Eric Mitchell, Stefano Ermon, Christopher D Manning, and Chelsea Finn · 2023
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Iglm: Infilling language modeling for antibody sequence design
Richard W Shuai, Jeffrey A Ruffolo, and Jeffrey J Gray · 2023
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De novo design of protein structure and function with rfdiffusion
Joseph L Watson, David Juergens, Nathaniel R Bennett, Brian L Trippe, Jason Yim, Helen E Eisenach, Woody Ahern, Andrew J Borst, Robert J Ragotte, Lukas F Milles, et al · 2023
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Helixdiff: Hotspot-specific full-atom design of peptides using diffusion models
Xuezhi Xie, Pedro A Valiente, Jisun Kim, and Philip M Kim · 2023
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Revolutionizing peptide-based drug discovery: Advances in the post-alphafold era
Liwei Chang, Arup Mondal, Bhumika Singh, Yisel Martínez-Noa, and Alberto Perez · 2024
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OpenAI · 2024
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A multi-modal contrastive diffusion model for therapeutic peptide generation, 2024
Yongkang Wang, Xuan Liu, Feng Huang, Zhankun Xiong, and Wen Zhang · 2024
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