ProGen2: Exploring the boundaries of protein language models

Cited by (496)

Items 101–200 of 496

  1. AI-driven innovation in antibody-drug conjugate design
    Heather A. Noriega, Xiang Simon Wang · 2025 · Frontiers in Drug Discovery
  2. Artificial intelligence in bioinformatics: a survey
    Jiyue Jiang, Yunke Li, Shiwei Cao, Yuheng Shan, Yuexing Liu, Tianyi Fei, Yule Yu, Yi Feng, Yu Li, Yixue Li et al. · 2025 · Briefings in Bioinformatics
  3. Protein Representation Learning via Knowledge Enhanced Primary Structure Modeling
    Hong-Yu Zhou, Yunxiang Fu, Zhicheng Zhang, Cheng Bian, Yizhou Yu · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
  4. Protein Language Model Fitness Is a Matter of Preference
    Cade Gordon, Amy X. Lu, Pieter Abbeel · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
  5. Recent advances in deep learning and language models for studying the microbiome
    Binghao Yan, Yunbi Nam, Lingyao Li, Rebecca A. Deek, Hongzhe Li, Siyuan Ma · 2025 · Frontiers in Genetics
  6. Variational autoencoder for design of synthetic viral vector serotypes
    Suyue Lyu, Shahin Sowlati‐Hashjin, Michael Garton · 2024 · Nature Machine Intelligence
  7. Adapting protein language models for structure-conditioned design
    Jeffrey A. Ruffolo, Aadyot Bhatnagar, Joel Beazer, Stephen Nayfach, Jordan Russ, Emily Hill, Riffat Hussain, Joseph P. Gallagher, Ali Madani · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
  8. Foundation models for bioinformatics
    Ziyu Chen, Lin Wei, Ge Gao · 2024 · Quantitative Biology
  9. Leveraging large language models for peptide antibiotic design
    Changge Guan, Fabiano C. Fernandes, Octávio Luiz Franco, César de la Fuente‐Núñez · 2024 · Cell Reports Physical Science
  10. Toward enhancement of antibody thermostability and affinity by computational design in the absence of antigen
    Hutchinson, Mark, Ruffolo, Jeffrey A., Haskins, Nantaporn, Iannotti, Michael, Vozza, Giuliana, Pham, Tony, Mehzabeen, Nurjahan, Shandilya, Harini, Rickert, Keith, Croasdale-Wood, Rebecca et al. · 2024 · mAbs
  11. PETA: evaluating the impact of protein transfer learning with sub-word tokenization on downstream applications
    Yang Tan, Mingchen Li, Ziyi Zhou, Pan Tan, Huiqun Yu, Guisheng Fan, Hong Liang · 2024 · Journal of Cheminformatics
  12. Training Compute-Optimal Protein Language Models
    Xingyi Cheng, Bo Chen, Pan Li, Jing Gong, Jie Tang, Le Song · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
  13. The Role of AI-Driven De Novo Protein Design in the Exploration of the Protein Functional Universe
    Guohao Zhang, Chuanyang Liu, Jiajie Lu, Shaowei Zhang, Lingyun Zhu · 2025 · Biology
  14. Discovery and protein language model-guided design of hyperactive transposases
    Dimitrije Ivančić, Alejandro Agudelo, Jonathan Lindstrom-Vautrin, Jessica Jaraba-Wallace, Maria Gallo, Ravi Das, Alejandro Ragel, Jorge Herrero-Vicente, Irene Higueras, Federico Billeci et al. · 2025 · Nature Biotechnology
  15. Semantical and geometrical protein encoding toward enhanced bioactivity and thermostability
    Tan, Yang, Zhou, Bingxin, Zheng, Lirong, Fan, Guisheng, Hong, Liang · 2025 · eLife
  16. Protein Design by Directed Evolution Guided by Large Language Models
    Thanh Phuoc Tran, Truong Son Hy · 2024 · IEEE Transactions on Evolutionary Computation
  17. p-IgGen: a paired antibody generative language model
    Oliver M. Turnbull, Dino Oglić, Rebecca Croasdale-Wood, Charlotte Mary Deane · 2024 · Bioinformatics
  18. LDBT instead of DBTL: combining machine learning and rapid cell-free testing
    Alia Clark‐ElSayed, Isa Madrigal Harrison, Meagan L. Olsen, John Tyler Lazar, Michael C. Jewett, Andrew D. Ellington · 2025 · Nature Communications
  19. Customizing CRISPR–Cas PAM specificity with protein language models
    Stephen Nayfach, Aadyot Bhatnagar, Andrey Novichkov, Nahye Kim, Alexander M. Hoffnagle, Riffat Hussain, Gabriella O. Estevam, Emily Hill, Jeffrey A. Ruffolo, Rachel A. Silverstein et al. · 2026 · Nature Biotechnology
  20. Deep learning in template-free de novo biosynthetic pathway design of natural products
    Xueying Xie, Lin Gui, Baixue Qiao, Guohua Wang, Shan Huang, Yuming Zhao, Shanwen Sun · 2024 · Briefings in Bioinformatics
  21. Non-Identifiability and the Blessings of Misspecification in Models of Molecular Fitness
    Eli N. Weinstein, Alan Amin, Jonathan Frazer, Debora S. Marks · 2022 · neural information processing systems
  22. Is Novelty Predictable?
    Clara Fannjiang, Jennifer Listgarten · 2023 · Cold Spring Harbor Perspectives in Biology
  23. PRESCOTT: a population aware, epistatic, and structural model accurately predicts missense effects
    Tekpinar, Mustafa, David, Laurent, Henry, Thomas, Carbone, Alessandra · 2025 · Genome Biology
  24. Evaluation of Machine Learning-Assisted Directed Evolution Across Diverse Combinatorial Landscapes
    Francesca-Zhoufan Li, Jason Yang, Kadina E. Johnston, Emre Gürsoy, Yisong Yue, Frances H. Arnold · 2024 · Cell Systems
  25. Understanding language model scaling for protein fitness prediction
    Chao Hou, Ди Лю, Aziz Zafar, Yufeng Shen · 2026 · Nature Computational Science
  26. A comprehensive overview of recent advances in generative models for antibodies
    Fanxu Meng, Na Zhou, Hu Guangchun, Ruotong Liu, Yuanyuan Zhang, Ming Jing, Qingzhen Hou · 2024 · Computational and Structural Biotechnology Journal
  27. A Survey of Large Language Model for Drug Research and Development
    Huijie Guo, Xudong Xing, Yongjie Zhou, Wenjiao Jiang, Xiaoyi Chen, Ting Wang, Zixuan Jiang, Yibing Wang, Junyan Hou, Yukun Jiang et al. · 2025 · IEEE Access
  28. Artificial intelligence driven protein design and sustainable nanomedicine for advanced theranostics
    Donya Esmaeilpour, Michael Richard Hamblin, Jianlin Cheng, Arezoo Khosravi, Jian Liu, Atefeh Zarepour, Ali Zarrabi, Mika Sillanpaa, Ehsan Nazarzadeh Zare‬, Jianliang Shen et al. · 2026 · Bioactive Materials
  29. How artificial intelligence is reengineering protein engineering
    Jennifer Listgarten, Hanlun Jiang · 2026 · Science
  30. Cutting-edge computational approaches in enzyme design and activity enhancement
    Ruobin Sun, Dan Wu, Pengcheng Chen, Pu Zheng · 2024 · Biochemical Engineering Journal
  31. GRACE: Generative Redesign in Artificial Computational Enzymology
    Ruei-En Hu, Chi‐Hua Yu, I‐Son Ng · 2024 · ACS Synthetic Biology
  32. Aggregating residue-level protein language model embeddings with optimal transport
    Navid Naderializadeh, Rohit Singh · 2024 · Bioinformatics Advances
  33. RNAGenesis: A Generalist Foundation Model for Functional RNA Therapeutics
    Zaixi Zhang, Ruofan Jin, Linlin Chao, Guangxue Xu, Yikun Zhang, Guowei Zhou, Di Yin, Yingqing Guo, Yaqi Fu, Yukang Yang et al. · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
  34. Foundation models of protein sequences: A brief overview
    Andreas Bjerregaard, Peter Mørch Groth, Søren Hauberg, Anders Krogh, Wouter Boomsma · 2025 · Current Opinion in Structural Biology
  35. FLAb2: Benchmarking reveals that protein AI models cannot yet consistently predict developability properties
    Michael Chungyoun, J. Robert Gray · 2026 · Patterns
  36. A comprehensive survey of genome language models in bioinformatics
    Liu Shu, Jiao Tang, Xiaoyu Guan, Daoqiang Zhang · 2025 · Briefings in Bioinformatics
  37. Plug & play directed evolution of proteins with gradient-based discrete MCMC
    Patrick Emami, Aidan Perreault, Jeffrey Law, David Biagioni, Peter C. St. John · 2023 · Machine Learning Science and Technology
  38. ESM-NBR: fast and accurate nucleic acid-binding residue prediction via protein language model feature representation and multi-task learning
    Wenwu Zeng, Dafeng Lv, Xuan Liu, Guo Chen, Wenjuan Liu, Shaoliang Peng · 2023 · IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
  39. Application of artificial intelligence large language models in drug target discovery
    Xinyu Liu, Jiafan Zhang, Xiaoran Wang, Maoda Teng, Guoying Wang, Xiaoming Zhou · 2025 · Frontiers in Pharmacology
  40. Programmable design of functional proteins from natural language
    Fengyuan Dai, Shiyang You, Yudian Zhu, Yuan Gao, Lihao Fu, Xibin Zhou, Jin Su, Chentong Wang, Yuliang Fan, Qingsong Tan et al. · 2026 · Nature
  41. Exploring the Protein Sequence Space with Global Generative Models
    Sergio Romero‐Romero, Sebastian Lindner, Noelia Ferruz · 2023 · Cold Spring Harbor Perspectives in Biology
  42. ESM All-Atom: Multi-scale Protein Language Model for Unified Molecular Modeling
    Kangjie Zheng, Siyu Long, Tianyu Lu, Junwei Yang, Xinyu Dai, Ming Zhang, Zaiqing Nie, Wei‐Ying Ma, Hao Zhou · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
  43. Scaling down protein language modeling with MSA Pairformer
    Yo Akiyama, Zhidian Zhang, Milot Mirdita, Martin Steinegger, Sergey Ovchinnikov · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  44. Computational design of novel Cas9 PAM-interacting domains using evolution-based modelling and structural quality assessment
    Malbranke, Cyril, Rostain, William, Depardieu, Florence, Cocco, Simona, Monasson, Rémi, Bikard, David · 2023 · PLOS Computational Biology
  45. MMFuncPhos: A Multi‐Modal Learning Framework for Identifying Functional Phosphorylation Sites and Their Regulatory Types
    Juan Xie, Ruihan Dong, Jintao Zhu, Haoyu Lin, Shiwei Wang, Luhua Lai · 2025 · Advanced Science
  46. Directed evolution of antimicrobial peptides using multi-objective zeroth-order optimization
    Xianliang Liu, Jiawei Luo, Xinyan Wang, Yang Zhang, Junjie Chen · 2024 · Briefings in Bioinformatics
  47. Language models for protein design
    Jin Seop Lee, Osama Abdin, Philip M. Kim · 2025 · Current Opinion in Structural Biology
  48. Advances in generative modeling methods and datasets to design novel enzymes for renewable chemicals and fuels
    Rana Ahmed Barghout, Zhi-Qing J. Xu, Siddharth Betala, Radhakrishnan Mahadevan · 2023 · Current Opinion in Biotechnology
  49. Toward deep learning sequence–structure co-generation for protein design
    Chentong Wang, Sarah Alamdari, Carles Domingo-Enrich, Ava P. Amini, Kevin Yang · 2025 · Current Opinion in Structural Biology
  50. SARITA: a large language model for generating the S1 subunit of the SARS-CoV-2 spike protein
    Simone Rancati, Giovanna Nicora, Laura Bergomi, Tommaso Mario Buonocore, Daniel M. Czyż, Enea Parimbelli, Riccardo Bellazzi, Marco Salemi, Mattia Prosperi, Simone Marini · 2025 · Briefings in Bioinformatics
  51. Uncovering the Genomic Manifold via Scalable Learning from the Global Microbiome
    Weimin Wu, Zhihan Zhou, Robert W. Riley, Mohammad Abdulqader, Xuefeng Song, Satria Ardhe Kautsar, Rob S Egan, Steven A. Hofmeyr, Gefei Liu, Shira Goldhaber-Gordon et al. · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  52. Large language models transform biological research: from architecture to utilization
    Wang, Tao, Luo, Zeyu · 2025 · Science China Information Sciences
  53. The Development Landscape of Large Language Models for Biomedical Applications
    Zhiyuan Cao, Vipina K. Keloth, Qianqian Xie, Lingfei Qian, Yuntian Liu, Yan Wang, Rui Shi, Weipeng Zhou, Gui Fen Yang, Jeffrey Zhang et al. · 2025 · Annual Review of Biomedical Data Science
  54. Foundation models in plant molecular biology: advances, challenges, and future directions
    Feng Xu, Tianhao Wu, Cheng Qian, Xiangfeng Wang, Jun Yan · 2025 · Frontiers in Plant Science
  55. AI sheds new light on genome editing
    Zhaohui Steve Qin, Zhaolong Deng, Chengwei Li, Daowen Wang, Xiang Ji, Zhen Chen · 2025 · Trends in biotechnology
  56. Fine-tuning protein language models unlocks the potential of underrepresented viral proteomes
    Sawhney, Rajan, Ferrell, Barbra D., Dejean, Thibaut, Schreiber, Zachary, Harrigan, William, Polson, Shawn W., Wommack, K. Eric, Belcaid, Mahdi · 2025 · PeerJ
  57. Advancing plant biology through deep learning-powered natural language processing
    Shuang Peng, Loïc Rajjou · 2024 · Plant Cell Reports
  58. Protein sequence modelling with Bayesian flow networks
    Timothy J. Atkinson, Thomas D. Barrett, Scott Cameron, Bora Guloglu, Matthew Greenig, Charlie B. Tan, Louis Robinson, Alex Graves, Liviu Copoiu, Alexandre Laterre · 2025 · Nature Communications
  59. Functional alignment of protein language models via reinforcement learning
    Nathaniel Blalock, Srinath Seshadri, Kensuke Nakamura, Agrim Babbar, Sarah A. Fahlberg, Ameya Kulkarni, Philip A. Romero · 2026 · Nature Communications
  60. 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)
  61. TCRdesign: an antigen-specific generative language model for de novo design of T-cell receptors
    Xiaokun Li, Qiang Yang, Long Xu, Weihe Dong, Kuanquan Wang, Suyu Dong, Wei Wang, Gongning Luo, Xianyu Zhang, Tiansong Yang et al. · 2025 · Briefings in Bioinformatics
  62. De novo design of functional nucleic acids of aptamers
    Zhiming Zhang, Meng Jiang, Axin He, Youyuan Zhu, Ercheng Wang, Liqi Wan, Jiezhong Qiu, Pei Guo, Guangyong Chen, Da Han · 2026 · Nature Computational Science
  63. The Dayhoff Atlas: scaling sequence diversity for improved protein generation
    Kevin Yang, Sarah Alamdari, Alex J. Lee, Kaeli Kaymak-Loveless, Samir Char, Garyk Brixi, Carles Domingo-Enrich, Chentong Wang, Suyue Lyu, Nicolò Fusi et al. · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  64. Quest for Orthologs in the era of Data Deluge and AI: Challenges and Innovations in Orthology Prediction and Data Integration
    Sina Majidian, Armin Hadziahmetovic, Felix Langschied, Stefano Pascarelli, Silvia Prieto-Baños, Jorge Rojas-Vargas, Lars Arvestad, Jitender Cheema, Salvatore Cosentino, Ingo Ebersberger et al. · 2025 · Journal of Molecular Evolution
  65. A survey on large language models in biology and chemistry
    Islambek Ashyrmamatov, Su Ji Gwak, Su-Young Jin, Ikhyeong Jun, Umit Volkan Ucak, Jay Yoon Lee, Juyong Lee · 2025 · Experimental & Molecular Medicine
  66. Evaluating Pretrained Protein Language Model Embeddings as Proxies for Functional Similarity
    Robert Shaw, Samuel D. Love, Claire D. McWhite · 2025 · Journal of Molecular Evolution
  67. Active learning-guided optimization of cell-free biosensors for lead testing in drinking water
    Brenda M. Wang, Nicole Chiang, Holly M. Ekas, Dylan M. Brown, Garrett Dildine, Tyler J. Lucci, Siyuan Feng, Vanessa Bly, Jean‐François Gaillard, Julius B. Lucks et al. · 2025 · Nature Communications
  68. Generalist biological artificial intelligence in modeling the language of life
    Vishwanatha Mitnala Rao, Serena Zhang, Brian S. Plosky, Patrick D. Hsu, Bo Wang, James Zou, Marinka Žitnik, Eric J. Topol, Pranav Rajpurkar · 2026 · Nature Biotechnology
  69. PandoGen: Generating complete instances of future SARS-CoV-2 sequences using Deep Learning
    A. Ramachandran, Steven S. Lumetta, Deming Chen · 2024 · PLoS Computational Biology
  70. DeepPLM_mCNN: An approach for enhancing ion channel and ion transporter recognition by multi-window CNN based on features from pre-trained language models
    Van‐The Le, Muhammad Shahid Malik, Yi-Hsuan Tseng, Yu‐Cheng Lee, Cheng-I Huang, Yu‐Yen Ou · 2024 · Computational Biology and Chemistry
  71. DeepAIP: Deep learning for anti-inflammatory peptide prediction using pre-trained protein language model features based on contextual self-attention network
    Lun Zhu, Qingguo Yang, Sen Yang · 2024 · International Journal of Biological Macromolecules
  72. VenusMutHub: A systematic evaluation of protein mutation effect predictors on small-scale experimental data
    Liang Zhang, Hua Pang, Chenghao Zhang, Song Li, Yang Tan, Fan Jiang, Mingchen Li, Yuanxi Yu, Ziyi Zhou, Banghao Wu et al. · 2025 · Acta Pharmaceutica Sinica B
  73. Recent advances and future trends for protein–small molecule interaction predictions with protein language models
    Alexander Kroll, Yvan Rousset · 2025 · Current Opinion in Structural Biology
  74. Machine-Guided Dual-Objective Protein Engineering for Deimmunization and Therapeutic Functions
    Eric Wolfsberg, Jean-Sebastien Paul, Josh Tycko, Binbin Chen, Michael Cory Bassik, Lacramioara Bintu, Ash A. Alizadeh, Xiaojing J. Gao · 2025 · Cell Systems
  75. Predictive and therapeutic applications of protein language models
    Kairi Furui, Koh Sakano, Masahito Ohue · 2025 · Allergology International
  76. FlowDesign: Improved design of antibody CDRs through flow matching and better prior distributions
    Wu, Jun, Kong, Xiangzhe, Sun, Ningguan, Wei, Jing, Shan, Sisi, Feng, Fuli, Wu, Feng, Peng, Jian, Zhang, Linqi, Liu, Yang et al. · 2025 · Cell Systems
  77. Human– AI partnerships: Living and working with AI Assistants, AI Agents, and AI Companions
    Ripinka Koli Patil, Dan Hamilton Rice, Chris A. Janiszewski · 2026 · Journal of Consumer Psychology
  78. For antibody sequence generative modeling, mixture models may be all you need
    Jonathan Parkinson, Wei Wang · 2024 · Bioinformatics
  79. Sequence-based generative AI design of versatile tryptophan synthases
    T Lambert, Amin Tavakoli, Gautham Dharuman, Jason Yang, Vignesh C. Bhethanabotla, Sukhvinder Kaur, Matthew Hill, Arvind Ramanathan, Animashree Anandkumar, Frances H. Arnold · 2026 · Nature Communications
  80. A generative foundation model for antibody sequence understanding
    Justin Barton, Aretas Gaspariunas, David Yadin, Jorge Dias, Francesca L. Nice, Danielle Minns, Olivia Snudden, Chelsea Povall, Sara Valle, Harry Dobson et al. · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
  81. TIMED-Design: flexible and accessible protein sequence design with convolutional neural networks
    Leonardo V. Castorina, Suleyman Mert Ünal, Kartic Subr, Christopher W. Wood · 2024 · Protein Engineering Design and Selection
  82. AI-accelerated therapeutic antibody development: practical insights
    Luca Santuari, Marianne Bachmann Salvy, Ioannis Xénarios, Alaaddin Bulak Arpat · 2024 · Frontiers in Drug Discovery
  83. S 2 ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning
    Mingze Yin, Hanjing Zhou, Jialu Wu, Yiheng Zhu, Yuxuan Zhan, Zitai Kong, Hongxia Xu, Chang‐Yu Hsieh, Jintai Chen, Tingjun Hou et al. · 2025 · Research
  84. SARS-CoV-2: lessons in virus mutation prediction and pandemic preparedness
    Weiyi Tang, Jenna Kim, Raphael TC Lee, Sebastian Maurer‐Stroh, Laurent Rénia, Matthew Zirui Tay · 2025 · Current Opinion in Immunology
  85. Engineering complexity into protein-based biomaterials for biomedical applications
    Nicole E. Gregorio, Cyrus M. Haas, Neil P. King, Cole A. DeForest · 2025 · Nature Reviews Materials
  86. PRO‐LDM: A Conditional Latent Diffusion Model for Protein Sequence Design and Functional Optimization
    Sitao Zhang, Zixuan Jiang, Rundong Huang, Wenting Huang, Siyuan Peng, Shaoxun Mo, Letao Zhu, Peiheng Li, Ziyi Zhang, Emily Pan et al. · 2025 · Advanced Science
  87. Evaluating variant effect prediction across viruses
    Sarah F. Gurev, Noor Youssef, Navami Jain, Aarushi Mehrotra, Sarrah Rose Mikhail Leung, Abigail Jackson, Debora S. Marks · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  88. A deep reinforcement learning platform for antibiotic discovery
    Hanqun Cao, Marcelo D. T. Torres, Jingjie Zhang, Zijun Gao, Fang Wu, Chunbin Gu, Jure Leskovec, Yejin Choi, César de la Fuente‐Núñez, Guangyong Chen et al. · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  89. Modeling Enzyme Kinetics: Current Challenges and Future Perspectives for Biocatalysis
    Jürgen Pleiss · 2024 · Biochemistry
  90. Identifying nucleotide-binding leucine-rich repeat receptor and pathogen effector pairing using transfer-learning and bilinear attention network
    Baixue Qiao, Shuda Wang, Mingjun Hou, Haodi Chen, Zhengwenyang Zhou, Xueying Xie, Shaozi Pang, Chunxue Yang, Fenglong Yang, Quan Zou et al. · 2024 · Bioinformatics
  91. Language models reveal a complex sequence basis for adaptive convergent evolution of protein functions
    Zhenqiu Cao, Hongjiu Zhang, Zhengting Zou · 2025 · Proceedings of the National Academy of Sciences
  92. A survey of downstream applications of evolutionary scale modeling protein language models
    Qingyu Yang, Jiale Yu, Jie Zheng · 2025 · Quantitative Biology
  93. Design of Stiff, Tough, and Fast‐Recovery Protein Hydrogels
    Ruiqing Wang, Yuan Gao, Wei Wang, Bin Xue, Yi Cao · 2025 · Chinese Journal of Chemistry
  94. Enhancing functional proteins through multimodal inverse folding with ABACUS-T
    Yufeng Liu, Rui Wu, Xinyu Wang, Sheng Wang, Ling-Hui Chen, Fudong Li, Quan Chen, Haiyan Liu · 2025 · Nature Communications
  95. Programmable Multiplex Genome Editing: Innovations in CRISPR Effectors, crRNA Engineering, and Delivery Strategies
    Gargi Bindal, Devashish Rath · 2025 · Synthetic biology and engineering
  96. Protein structure prediction powered by artificial intelligence: from biochemical foundations to practical applications
    Tianxiang Yin, Yunxuan Chen, Yuhang Wang, Hui Su, Chengxu Duan, Jingrui Liu · 2026 · Frontiers in Molecular Biosciences
  97. Multimodal learning of heat capacity based on transformers and crystallography pretraining
    Hongshuo Huang, Amir Barati Farimani · 2024 · Journal of Applied Physics
  98. Reprogramming pretrained language models for protein sequence representation learning
    Ria Vinod, Pin‐Yu Chen, Payel Das · 2025 · Digital Discovery
  99. InstructPLM: Aligning Protein Language Models to Follow Protein Structure Instructions
    Jiezhong Qiu, Junde Xu, Jie Hu, Hanqun Cao, Liya Hou, Zi-Jun Gao, Xinyi Zhou, Anni Li, Xiujuan Li, Bin Cui et al. · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
  100. LC-PLM: Long-context Protein Language Modeling Using Bidirectional Mamba with Shared Projection Layers
    Yingheng Wang, Zichen Wang, Gil Sadeh, Luca Zancato, Alessandro Achille, George Karypis, Huzefa Rangwala · 2024 · bioRxiv (Cold Spring Harbor Laboratory)