Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences

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Items 901–1,000 of 1,006

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    Yingwen Zhao, Zhihao Yang, Yongkai Hong, Yumeng Yang, Lei Wang, Yin Zhang, Hongfei Lin, Jian Wang · 2023 · IEEE Transactions on NanoBioscience
15. Protein engineering of pores for separation, sensing, and sequencing
    Laxmicharan Samineni, Bibek Acharya, Harekrushna Behera, Hyeonji Oh, Manish Kumar, Ratul Chowdhury · 2023 · Cell Systems
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    Tong Zhu, Jinyuan Sun, Hua Pang, Bian Wu · 2024 · JACS Au
20. A comprehensive computational benchmark for evaluating deep learning-based protein function prediction approaches
    Wenkang Wang, Yunyan Shuai, Qiurong Yang, Fuhao Zhang, Min Zeng, Min Li · 2024 · Briefings in Bioinformatics
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    Jason Chen, Ayisha Zia, Albert Luo, Hanze Meng, Fengbin Wang, Jie Hou, Renzhi Cao, Dong Si · 2024 · Briefings in Bioinformatics
22. Protein function prediction through multi-view multi-label latent tensor reconstruction
    Robert Ebo Armah-Sekum, Sándor Szedmák, Juho Rousu · 2024 · BMC Bioinformatics
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    Mahmood Kalemati, Mojtaba Zamani Emani, Somayyeh Koohi · 2024 · BMC Genomics
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25. Machine learning for predicting protein properties: A comprehensive review
    Yizhen Wang, Yanyun Zhang, Xuhui Zhan, Yuhao He, Yongfu Yang, Li Cheng, Daniyal Alghazzawi · 2024 · Neurocomputing
26. Improving protein function prediction by learning and integrating representations of protein sequences and function labels
    Frimpong Boadu, Jianlin Cheng · 2024 · Bioinformatics Advances
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    Feng, Mofan, Wei, Xiaoxi, Zheng, Xi, Liu, Liangjie, Lin, Lin, Xia, Manying, He, Guang, Shi, Yi, Lu, Qing · 2024 · Nature Communications
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    Muhammad Nabeel Asim, Muhammad Ali Ibrahim, Tayyaba Asif, Andreas R. Dengel · 2025 · Heliyon
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    Atabey Ünlü, Erva Ulusoy, Melih Gökay Yiğit, Melih Darcan, Tunca Doğan · 2025 · Current Opinion in Structural Biology
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    Navid Naderializadeh, Rohit Singh · 2024 · Bioinformatics Advances
31. Bayesian optimization with evolutionary and structure-based regularization for directed protein evolution
    Trevor S. Frisby, CHRISTOPHER JAMES LANGMEAD · 2021 · Algorithms for Molecular Biology
32. PSSM-Distil: Protein Secondary Structure Prediction (PSSP) on Low-Quality PSSM by Knowledge Distillation with Contrastive Learning
    Qin Wang, Boyuan Wang, Zhenlei Xu, Jiaxiang Wu, Peilin Zhao, Zhen Li, Sheng Wang, Junzhou Huang, Shuguang Robert Cui · 2021 · Proceedings of the AAAI Conference on Artificial Intelligence
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    Remo Monti, Pia Rautenstrauch, Mahsa Ghanbari, Alva Rani James, Matthias Kirchler, Uwe Ohler, Stefan Konigorski, Christoph Lippert · 2022 · Nature Communications
34. A primer on model-guided exploration of fitness landscapes for biological sequence design
    Sam Sinai, Eric D. Kelsic · 2020 · arXiv (Cornell University)
35. Generating novel protein sequences using Gibbs sampling of masked language models
    Sean R. Johnson, Sarah Monaco, Kenneth Massie, Zaid Syed · 2021 · bioRxiv (Cold Spring Harbor Laboratory)
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    Hongyu Shen, Layne C. Price, Mohammad Taha Bahadori, Franziska Seeger · 2021 · bioRxiv (Cold Spring Harbor Laboratory)
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    Rohit Singh, Chiho Im, Yu Qiu, Brian C. Mackness, Abhinav Gupta, Taylor Sorenson, Samuel Sledzieski, Lena Erlach, Maria Wendt, Yves Fomekong‐Nanfack et al. · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
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    Novikov, Alexander, Vũ, Ngân, Eisenberger, Marvin, Dupont, Emilien, Huang, Po-Sen, Wagner, Adam Zsolt, Shirobokov, Sergey, Kozlovskii, Borislav, Ruiz, Francisco J. R., Mehrabian, Abbas et al. · 2025 · arXiv
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    Totaro, Massimo G., Vide, Uršula, Zausinger, Regina, Winkler, Andreas, Oberdorfer, Gustav · 2024 · Protein Science
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    Li, Yi-Fan, Pan, Xiaoyong, Shen, Hong-Bin · 2025 · Patterns
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    Yang Tan, Rui-Lin Wang, Banghao Wu, Liang Hong, Bingxin Zhou · 2025 · Bioinform.
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    Haoran Peng, Angel Jonathan Ruiz-Moreno, Jingyuan Fu · 2025 · Nature Reviews Bioengineering
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    Artem Gazizov, Anna Lian, Casper A. Goverde, Jody Mou, Sergey Ovchinnikov, Nicholas F. Polizzi · 2026 · Nature Methods
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    Yunan Luo, Lam Tung Vo, Hantian Ding, Yufeng Su, Yang Liu, Wesley Wei Qian, Huimin Zhao, Jian Peng · 2020 · Lecture notes in computer science
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    Dingkai Huang, Hongjian He, Jiaming Ouyang, Chang Zhao, Xin Wen Dong, Jiang Xie · 2022 · BMC Bioinformatics
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    Yixuan Shu, Yanru Hai, Lihua Cao, Jianmin Wu · 2023 · Computational and Structural Biotechnology Journal
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    Xin Wang, Xin Gao, Guohua Wang, Dan Li · 2023 · Briefings in Bioinformatics
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    Felix Teufel, Jan C. Refsgaard, Christian T. Madsen, Carsten Stahlhut, Mads Grønborg, Ole Winther, Dennis Madsen · 2023 · Bioinformatics
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    Zi-Sin Yang, Tzong-Shiun Li, Yu-Sung Huang, Cheng‐Chung Chang, Ching‐Ming Chien · 2024 · Scientific Reports
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    Meili Cui, Mengyue Wang, Haoyan Sun, Lu Yu, Zhenhua Su, Xiaofeng Zhang, Yu Zheng, Menglei Xia, Yanbing Shen, Min Wang · 2024 · International Journal of Biological Macromolecules
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    Zhaowei Wang, Jun Meng, Qiguo Dai, Haibin Li, Shihao Xia, Ruirui Yang, Yushi Luan · 2024 · Expert Systems with Applications
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    Artur Hermano Sampaio Dias, Yuanxin Cao, Munir S. Skaf, Sam P. de Visser · 2024 · Physical Chemistry Chemical Physics
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    Hanyu Zhang, Yuan Zhou, Zhichao Zhang, Huaicheng Sun, Ziqi Pan, Minjie Mou, Wei Zhang, Qing Ye, Tingjun Hou, Honglin Li et al. · 2024 · Analytical Chemistry
60. In the twilight zone of protein sequence homology: do protein language models learn protein structure?
    Anowarul Kabir, Asher Moldwin, Yana Bromberg, Amarda Shehu · 2024 · Bioinformatics Advances
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    Yu-Jen Lin, Arul S. Menon, Zhiqiang Hu, Steven E. Brenner · 2024 · Human Genomics
62. GORetriever: reranking protein-description-based GO candidates by literature-driven deep information retrieval for protein function annotation
    Huiying Yan, Shaojun Wang, Hancheng Liu, Hiroshi Mamitsuka, Shanfeng Zhu · 2024 · Bioinformatics
63. SSR-DTA: Substructure-aware multi-layer graph neural networks for drug–target binding affinity prediction
    Yuansheng Liu, Xinyan Xia, Yongshun Gong, Bosheng Song, Xiangxiang Zeng · 2024 · Artificial Intelligence in Medicine
64. DeepNeoAG: Neoantigen epitope prediction from melanoma antigens using a synergistic deep learning model combining protein language models and multi-window scanning convolutional neural networks
    Cheng-Che Chuang, Yuchen Liu, Yu‐Yen Ou · 2024 · International Journal of Biological Macromolecules
65. Large language models transform biological research: from architecture to utilization
    Wang, Tao, Luo, Zeyu · 2025 · Science China Information Sciences
66. SensorFormer: Efficient Many-to-Many Sensor Calibration With Learnable Input Subsampling
    Yun Cheng, Olga Saukh, Lothar Thiele · 2022 · IEEE Internet of Things Journal
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    Jérôme Tubiana, Dina Schneidman‐Duhovny, Haim J. Wolfson · 2022 · Journal of Molecular Biology
68. Advancing variant effect prediction using protein language models
    Benjamin Livesey, Joseph A. Marsh · 2023 · Nature Genetics
69. Profile Prediction: An Alignment-Based Pre-Training Task for Protein Sequence Models
    Pascal Sturmfels, Jesse Vig, Ali Madani, Nazneen Fatema Rajani · 2020 · arXiv (Cornell University)
70. Pre-training Protein Language Models with Label-Agnostic Binding Pairs Enhances Performance in Downstream Tasks
    Modestas Filipavicius, Matteo Manica, Joris Cadow, María Rodríguez Martínez · 2020 · arXiv (Cornell University)
71. Now What Sequence? Pre-trained Ensembles for Bayesian Optimization of Protein Sequences
    Ziyue Yang, Katarina A. Milas, Andrew D. White · 2022 · bioRxiv (Cold Spring Harbor Laboratory)
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    Raman Samusevich, Safa Mert Akmeşe, Téo Hebra, Roman Bushuiev, Martin Engst, Jonáš Kulhánek, Anton Bushuiev, Joshua D. Smith, Tereza Čalounová, Helena Smrčková et al. · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
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    Kulikova, Anastasiya V., Diaz, Daniel J., Chen, Tianlong, Cole, T. Jeffrey, Ellington, Andrew D., Wilke, Claus O. · 2023 · Scientific Reports
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    Xu, Shijie, Onoda, Akira · 2025 · Journal of Chemical Theory and Computation
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    Xin Wang, Yuan Liu, Zhenchao Wang, Xiangmei Zeng, William Shu Ching Ngai, Jie Wang, Heng Zhang, Xiao Xie, Rongfeng Zhu, Xinyuan Fan et al. · 2025 · Cell
77. AIR-Nets: An Attention-Based Framework for Locally Conditioned Implicit Representations
    Simon Giebenhain, Bastian Goldlüecke · 2021 · International Conference on 3D Vision (3DV)
78. Running ahead of evolution—AI-based simulation for predicting future high-risk SARS-CoV-2 variants
    Jie Chen, Zhiwei Nie, Yu Wang, Kai Wang, Fan Xu, Zhiheng Hu, Bing Zheng, Zhennan Wang, Guoli Song, Jingyi Zhang et al. · 2023 · The International Journal of High Performance Computing Applications
79. Predicting Protein Functions Based on Heterogeneous Graph Attention Technique
    Yingwen Zhao, Zhihao Yang, Lei Wang, Yin Zhang, Hongfei Lin, Jian Wang · 2024 · IEEE Journal of Biomedical and Health Informatics
80. Combining Rosetta Sequence Design with Protein Language Model Predictions Using Evolutionary Scale Modeling (ESM) as Restraint
    Moritz Ertelt, Jens Meiler, Clara T. Schoeder · 2024 · ACS Synthetic Biology
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82. SOFB is a comprehensive ensemble deep learning approach for elucidating and characterizing protein-nucleic-acid-binding residues
    Bin Zhang, Zilong Hou, Yuning Yang, Ka‐Chun Wong, Haoran Zhu, Xiangtao Li · 2024 · Communications Biology
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    Francesca Cuturello, Marco Celoria, Alessio Ansuini, Alberto Cazzaniga · 2024 · Bioinformatics
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    Margarita Pertseva, Océane M. Follonier, Daniele Scarcella, Sai T. Reddy · 2024 · Briefings in Bioinformatics
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    Jianda Yue, Jiawei Xu, Tingting Li, Yaqi Li, Zihui Chen, Songping Liang, Zhonghua Liu, Ying Wang · 2024 · Computers in Biology and Medicine
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    Hongsong Feng, Li Shen, Jian Liu, Guo-Wei Wei · 2024 · Journal of Computational Biophysics and Chemistry
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    Lingrong Zhang, Taigang Liu · 2024 · International Journal of Biological Macromolecules
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    Zhaohui Qin, Haoran Ren, Pei Zhao, Kaiyuan Wang, Huixia Liu, Chunbo Miao, Yanxiu Du, Junzhou Li, Liuji Wu, Zhen Chen · 2024 · Briefings in Bioinformatics
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    Meshari Alazmi · 2024 · Frontiers in Artificial Intelligence
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    Hongwei Xia, Caiyue Dong, Xinxing Chen, Zhuoyu Wei, Lichuan Gu, Xiaolei Zhu · 2024 · BMC Genomics
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    Ramon, Aubin, Ni, Mingyang, Predeina, Olga, Gaffey, Rebecca, Kunz, Patrick, Onuoha, Shimobi, Sormanni, Pietro · 2025 · mAbs
95. Enhanced prediction of protein functional identity through the integration of sequence and structural features
    Fujita, Suguru, Terada, Tohru · 2024 · Computational and Structural Biotechnology Journal
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    Sawhney, Rajan, Ferrell, Barbra D., Dejean, Thibaut, Schreiber, Zachary, Harrigan, William, Polson, Shawn W., Wommack, K. Eric, Belcaid, Mahdi · 2025 · PeerJ
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    Tan, Yang, Zhou, Bingxin, Zheng, Lirong, Fan, Guisheng, Hong, Liang · 2025 · eLife
98. Ultrafast end-to-end protein structure prediction enables high-throughput exploration of uncharacterised proteins
    Kandathil, Shaun M, Greener, Joe G, Lau, Andy M, Jones, David T · 2020
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     Zhang, Yumeng, Zheng, Jared, Zhang, Bin · 2025 · eLife