Modeling the language of life – Deep Learning Protein Sequences

Cited by (599)

Items 401–500 of 599

1. GTPLM-GO: Enhancing Protein Function Prediction Through Dual-Branch Graph Transformer and Protein Language Model Fusing Sequence and Local–Global PPI Information
   Haotian Zhang, Yundong Sun, Yansong Wang, Xiaoling Luo, Yumeng Liu, Bin Chen, Xiaopeng Jin, Dongjie Zhu · 2025 · International Journal of Molecular Sciences
2. Organizing the bacterial annotation space with amino acid sequence embeddings
   Susanna R. Grigson, Jody C. McKerral, James G. Mitchell, Robert Alan Edwards · 2022 · BMC Bioinformatics
3. Navigating the amino acid sequence space between functional proteins using a deep learning framework
   Tristan Bitard‐Feildel · 2021 · PeerJ Computer Science
4. SPOT-Contact-Single: Improving Single-Sequence-Based Prediction of Protein Contact Map using a Transformer Language Model
   Jaspreet Singh, Thomas Litfin, Jaswinder Singh, Kuldip K. Paliwal, Yaoqi Zhou · 2021 · bioRxiv (Cold Spring Harbor Laboratory)
5. Sequential Labelling and DNABERT For Splice Site Prediction in Homo Sapiens DNA
   Muhammad Anwari Leksono, Ayu Purwarianti · 2023 · Research Square
6. What the protein!? Computational methods for predicting microbial protein functions
   Susanna R. Grigson, Robert P. Edwards · 2023 · OSF Preprints (OSF Preprints)
7. Context-Aware Amino Acid Embedding Advances Analysis of TCR-Epitope Interactions
   Pengfei Zhang, Seojin Bang, Michael Cai, Heewook Lee · 2024 · eLife
8. Artificial Intelligence Learns Protein Prediction
   Michael Heinzinger, Burkhard Rost · 2024 · Cold Spring Harbor Perspectives in Biology
9. Multimodal graph, surface, and language-based model for protein protein interaction prediction
   Arteaga, David, Chervov, Nikita, Poptsova, Maria · 2026 · Scientific Reports
10. Comparative Analysis on Alignment-Based and Pretrained Feature Representations for the Identification of DNA-Binding Proteins
    Die Chen, Hua Zhang, Zeqi Chen, Bo Xie, Ye Wang · 2022 · Computational and Mathematical Methods in Medicine
11. PRONTO-TK: a user-friendly PROtein Neural neTwOrk tool-kit for accessible protein function prediction
    Gianfranco Michele Maria Politano, Alfredo Benso, Hafeez Ur Rehman, Angela Re · 2024 · NAR Genomics and Bioinformatics
12. Machine Learning Techniques to Infer Protein Structure and Function from Sequences: A Comprehensive Review
    Gopal Narayan Srivastava, Mengmeng Liu, Xialong Ni, Limeng Pu, Michał Bryliński · 2024 · Methods in molecular biology
13. Inferring context-specific site variation with evotuned protein language models
    Spyros Lytras, Adam Patrick Strange, Jumpei Ito, Kei Sato · 2026 · NAR Genomics and Bioinformatics
14. Structure-based analyses of gut microbiome-related proteins by neural networks and molecular dynamics simulations
    Kei Taneishi, Yuko Tsuchiya · 2022 · Current Opinion in Structural Biology
15. Identification of plant vacuole proteins by using graph neural network and contact maps
    Jianan Sui, Jiazi Chen, Yuehui Chen, Naoki Iwamori, Jin Sun · 2023 · BMC Bioinformatics
16. PEvoLM: Protein Sequence Evolutionary Information Language Model
    Issar Arab · 2023 · IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)
17. PDB2Vec: Using 3D Structural Information for Improved Protein Analysis
    Sarwan Ali, Prakash Chourasia, Murray Patterson · 2023 · Lecture notes in computer science
18. ILMCNet: A Deep Neural Network Model That Uses PLM to Process Features and Employs CRF to Predict Protein Secondary Structure
    Benzhi Dong, Hui Su, Dali Xu, Chang Hou, Zheng Liu, Na Niu, Guohua Wang · 2024 · Genes
19. Impact of Alignments on the Accuracy of Protein Subcellular Localization Predictions
    Maryam Gillani, Gianluca Pollastri · 2024 · Proteins Structure Function and Bioinformatics
20. MEGA-GO: functions prediction of diverse protein sequence length using Multi-scalE Graph Adaptive neural network
    Yujian Lee, Peng Gao, Yongqi Xu, Ziyang Wang, Shuai Cheng Li, Jiaxing Chen · 2025 · Bioinformatics
21. PPI Prediction from Sequences via Transfer Learning on Balanced but yet Biased Datasets: An Open Problem
    Alba Nogueira-Rodríguez, Daniel Glez‐Peña, Cristina P. Vieira, Jorge Vieira, Hugo López-Fernández · 2025 · Lecture notes in networks and systems
22. Align-gram: Rethinking the Skip-gram Model for Protein Sequence Analysis
    Nabil Ibtehaz, S. M. Shakhawat Hossain Sourav, Md. Shamsuzzoha Bayzid, M. Sohel Rahman · 2023 · The Protein Journal
23. Ion channel classification through machine learning and protein language model embeddings
    Hamed Ghazikhani, Gregory Butler · 2024 · Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics
24. Augmenting protein network embeddings with sequence information
    Hassan Kané, Mohamed Coulibali, Ali Abdalla, Pelkins Ajanoh · 2019 · bioRxiv (Cold Spring Harbor Laboratory)
25. Localnet: A Simple Recurrent Neural Network Model for Protein Secondary Structure Prediction Using Local Amino Acid Sequences Only
    Shutong Yang, Yuhong Wang, Kennie Cruz-Gutierrez, Fangling Wu, Chuan‐Fan Ding · 2021 · Research Square
26. Simple End-to-end Deep Learning Model for CDR-H3 Loop Structure Prediction
    Natalia Zenkova, Sedykh, Ekaterina, Tatiana E. Shugaeva, Vladislav Strashko, Timofei Ermak, Aleksei Shpilman · 2021 · arXiv (Cornell University)
27. OpenProteinSet: Training data for structural biology at scale.
    Gustaf Ahdritz, Nazim Bouatta, Sachin Kadyan, Lukas Jarosch, Daniel Berenberg, I. Fisk, Andrew M. Watkins, Stephen Ra, Richard Bonneau, Mohammed AlQuraishi · 2023 · PubMed
28. Combining Directed Evolution with Machine Learning Enables Accurate Genotype-to-Phenotype Predictions
    Alexander J. Howard, Ellen Youngsoo Rim, Oscar D. Garrett, Yejin Shim, James H. Notwell, Pamela C. Ronald · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
29. The AI Revolution in Chemistry: Shaping the Future of Materials and Biomedical Sciences
    Bhuvaneshwari S Baranwal, Leighton O. Jones, Ankush Maind, Umesh Balande, Dipratn G. Khandare, Hina Goyal, Leilani M. Lotti Diaz, Julian M. Ivanov, Qiongqiong Angela Zhou · 2025 · ChemRxiv
30. PPILS: Protein-protein interaction prediction with language of biological coding
    Nayan Howladar, Md Wasi Ul Kabir, Foyzul Hoque, Ataur Katebi, Md Tamjidul Hoque · 2025 · Computers in Biology and Medicine
31. Towards a more accurate and reliable evaluation of machine learning protein–protein interaction prediction model performance in the presence of unavoidable dataset biases
    Alba Nogueira-Rodríguez, Daniel Glez‐Peña, Cristina P. Vieira, Jorge Vieira, Hugo López-Fernández · 2025 · Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics
32. BERTPVP: Identifying and Classifying Phage Virion Proteins Using Bidirectional Encoder Representations-Based Transformers
    Lijia Ma, Wenxiang Zhou, Yuan Bai, Min Fang, Minfeng Xiao, Jianqiang Li · 2025 · IEEE Transactions on Computational Biology and Bioinformatics
33. Progress and challenges for the application of machine learning for neglected tropical diseases
    ChungYuen Khew, Rahmad Akbar, Norfarhan Mohd‐Assaad · 2025 · F1000Research
34. Graph Neural Network-Based Approaches for Protein Function Prediction
    Meenal Chaudhari, Soufia Bahmani, Pawel Pratyush, Steven Garrett, Neel J Thapa, Dukka B. KC · 2025 · Methods in molecular biology
35. Binding Stability and Catalytic Mechanism of a Novel Chitin Deacetylase from Cytobacillus firmus and Preparation of Chitosan
    Bicheng Liang, Tong Zhang, Guantian Li, Haoyue Yang, Zongji Wang, Kecheng Li, Song Liu, Huahua Yu, Ronge Xing · 2025 · Journal of Agricultural and Food Chemistry
36. SeqDA-HLA: Language Model and Dual Attention-Based Network to Predict Peptide-HLA Class I Binding
    Gihyeon Kim, Geonhui Jo, Minjeong Kim, Soo Young Cho, Jang‐Hwan Choi · 2025 · IEEE Transactions on Computational Biology and Bioinformatics
37. Enhancing cross-domain protein and peptide interaction with retrained deep learning models
    Xin Cao, Jingquan Li, Fanpeng Meng, Bing Yang, Yanyan Zou · 2025 · Briefings in Bioinformatics
38. PPEPFinder : A deep learning framework integrating sequence embeddings and structural graph representations for predicting fungal and oomycete effector proteins
    Mengdi Yuan, Shaoke Zhang, Jiajun Li, Jingyan Zheng, Chenping Lei, Zhuojun Wang, Miao Zhao, Wenyu Shi, Ziding Zhang · 2025 · The Plant Journal
39. Design of a Labile RNase A Using Protein Language Models
    Gabriel Ong, Kiat Whye Kong, Si En Poh, Fong Tian Wong, Yiqi Seow, Winston Lian Chye Koh · 2025 · ACS Synthetic Biology
40. Prediction of protein-protein interactions using point transformer and spherical Convex Hull graphs
    David Arteaga, Maria S. Poptsova · 2025 · Computational and Structural Biotechnology Journal
41. Struct2GO-Enhanced: Multimodal Graph Attention Improves Protein Function Prediction
    Zihan Shi, Thanh Hoa Vo, Nguyen Quoc Khanh Le, Matthew Chin Heng Chua · 2026 · Journal of Chemical Information and Modeling
42. DeepPFT-GANCap: An explainable attention-based hybrid deep learning framework integrating protein language models and wavelet denoising-based evolutionary features for photosystem-II core protein prediction
    Wajdi Alghamdi, Farman Ali, Abdulmohsen Algarni, Omar Alghushairy, Majdi Khalid, Meng‐Ze Du · 2026 · Ecological Informatics
43. Machine Learning-Driven Simulations of the SARS-CoV-2 Fitness Landscape from Deep Mutational Scanning Experiments
    Aleksander E. P. Durumeric, Sean McCarty, Jay Smith, Jonas Köhler, Katarina Elez, Lluı́s Raich, Patricia Suriana, Terra Sztain · 2026 · Journal of Chemical Information and Modeling
44. Enhancing protein immunogenicity prediction via uncertainty weighted deep ensemble
    Alif Bin Abdul Qayyum, Amir Hossein Rahmati, Xiaoning Qian, Byung-Jun Yoon · 2026 · Oxford Open Immunology
45. CLABP: a contrastive learning framework integrating protein language models and structural information for antibacterial peptide prediction
    Xiangrun Zhou, Guixia Liu, Ji Lv · 2026 · Briefings in Bioinformatics
46. Pro4S : Prediction of protein solubility by fusing sequence, structure, and surface
    Jie Qian, Lin Yang, Renxiao Wang, Yifei Qi · 2026 · Protein Science
47. Accurate Identification of Submitochondrial Protein Location Based on Deep Representation Learning Feature Fusion
    Jianan Sui, Yuehui Chen, Yi Cao, Yaou Zhao · 2023 · Lecture notes in computer science
48. Gaussian Beltrami-Klein Model for Protein Sequence Classification: A Hyperbolic Approach
    Sarwan Ali, Haris Mansoor, Prakash Chourasia, Yasir Ali, Murray Patterson · 2024 · Lecture notes in computer science
49. An experimental analysis of graph representation learning for Gene Ontology based protein function prediction
    Thi Thuy Duong Vu, Jeongho Kim, Jaehee Jung · 2024 · PeerJ
50. Hist2Vec: A histogram and kernel-based embedding method for molecular sequence analysis
    Sarwan Ali, Tamkanat E. Ali, Haris Mansoor, Prakash Chourasia, Murray Patterson · 2025 · Expert Systems with Applications
51. Enhancing the Feature Representation of Protein Sequence Descriptors in Protein-Protein Interaction Prediction
    Hoai-Nhan Tran, Nguyen-Phuc-Xuan Quynh, Haochen Zhao, Jianxin Wang · 2025 · Interdisciplinary Sciences Computational Life Sciences
52. DeepPWM-BindingNet: Unleashing Binding Prediction with Combined Sequence and PWM Features
    Sarwan Ali, Prakash Chourasia, Murray Patterson · 2025 · Communications in computer and information science
53. Position Specific Scoring Is All You Need? Revisiting Protein Sequence Classification Tasks
    Sarwan Ali, Taslim Murad, Prakash Chourasia, Haris Mansoor, Imdadullah Khan, Pin‐Yu Chen, Murray Patterson · 2025 · Lecture notes in computer science
54. Interpretable Prediction of SARS-CoV-2 Epitope-Specific TCR Recognition Using a Pre-Trained Protein Language Model
    Sunyong Yoo, Myeonghyeon Jeong, Subhin Seomun, Kiseong Kim, Youngmahn Han · 2024 · IEEE Transactions on Computational Biology and Bioinformatics
55. Protein Secondary Structure Prediction using N-Grams and 1-Dimensional Convolutional Neural Network
    Annisa Rizqiana, Afiahayati · 2024 · Joint International Conference on Soft Computing and Intelligent Systems and International Symposium on Advanced Intelligent Systems (SCIS&ISIS)
56. Trainable subnetworks reveal insights into structure knowledge organization in protein language models
    Ria Vinod, Ava P. Amini, Lorin A. Crawford, Kevin Yang · 2026 · PLoS Computational Biology
57. A Review of Extremophile Protein Classification Using Machine Learning
    Meredita Susanty, Tati Latifah Erawati Rajab, Rukman Hertadi · 2022 · International Conference on Wireless and Telematics (ICWT)
58. Learning the Protein Language Model of SARS-CoV-2 Spike Proteins
    Paul Vincent Llanes, Geoffrey A. Solano, Marc Jermaine Pontiveros · 2023 · International Conference on Artificial Intelligence in Information and Communication (ICAIIC)
59. A Comparative Analysis of Transformer-based Protein Language Models for Remote Homology Prediction
    Anowarul Kabir, Asher Moldwin, Amarda Shehu · 2023 · ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB)
60. A Universal Non-parametric Approach for Improved Molecular Sequence Analysis
    Sarwan Ali, Tamkanat E. Ali, Prakash Chourasia, Murray Patterson · 2024 · Lecture notes in computer science
61. Self-Supervised Representation Learning of Protein Tertiary Structures (PtsRep) and Its Implications for Protein Engineering
    Junwen Luo, Yi Cai, Jialin Wu, Hongmin Cai, Xiaofeng Yang, Zhanglin Lin · 2020 · bioRxiv (Cold Spring Harbor Laboratory)
62. Refining Embedding-Based Binding Predictions by Leveraging AlphaFold2 Structures
    Leopold Endres, Tobias Olenyi, Kyra Erckert, Konstantin Weißenow, Burkhard Rost, Maria Littmann · 2022 · bioRxiv (Cold Spring Harbor Laboratory)
63. ntEmbd: Deep learning embedding for nucleotide sequences
    Saber Hafezqorani, Ka Ming Nip, İnanç Birol · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
64. Phylogeny-informed transfer learning with protein language models for epitope prediction
    Lindeberg Pessoa Leite, Teófilo Emidio de Campos, Francisco Pereira Lobo, Felipe Campelo · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
65. Protein Language Modeling beyond static folds reveals sequence-encoded flexibility
    Finn H. Lüth, Victor Mihaila, Milot Mirdita, Martin Steinegger, Burkhard Rost, Michael Heinzinger · 2026 · bioRxiv (Cold Spring Harbor Laboratory)
66. The rise of the machines in chemistry
    Michelle L. Gill · 2022 · Magnetic Resonance in Chemistry
67. Highly Accurate Protein Structure Classification and Prediction
    Anirban Saha, Indranil Sarkar · 2023 · International Conference on Computational Systems and Communication (ICCSC)
68. Combining handcrafted and learned features using deep learning to improve protein-protein interaction prediction performance
    Hoai-Nhan Tran, Nguyen Phuc Xuan Quynh, Lê Anh Phương · 2024 · Journal of Information and Telecommunication
69. Machine Learning for Protein Function Prediction
    Yi-Heng Zhu, Zi Liu, Yu Qing Ding, Zhiwei Ji, Dong-Jun Yu · 2025 · Methods in molecular biology
70. Progress and challenges for the application of machine learning for neglected tropical diseases
    ChungYuen Khew, Rahmad Akbar, Norfarhan Mohd‐Assaad · 2025 · F1000Research
71. Exploring homology detection via k-means clustering of proteins embedded with a large language model
    Thomas Minotto, Antoine Claessens, Thomas D. Otto · 2025 · Bioinformatics
72. DeepSaltPro: Enhancing halophilic protein prediction accuracy and efficiency via multi-protein language model integration
    Yuxin Xia, Qi Guo, Taigang Liu · 2025 · International Journal of Biological Macromolecules
73. Mining channel-regulated peptides from animal venom by integrating sequence semantics and structural information
    Jianming Wang, Rong-Kai Cui, Zheng-Kun Qian, Zizhong Yang, Yi Li · 2024 · Computational Biology and Chemistry
74. Hilbert Curve Based Molecular Sequence Analysis
    Sarwan Ali, Tamkanat E. Ali, Imdadullah Khan, Murray Patterson · 2025 · Lecture notes in computer science
75. Large Context, Deeper Insights: Harnessing Large Language Models for Advancing Protein–Protein Interaction Analysis
    U Kaicheng, Sophia Meixuan Zhang, Suresh Pokharel, Pawel Pratyush, Farah Qaderi, Dongfang Liu, Junhan Zhao, Dukka B. KC, Siwei Chen · 2025 · Methods in molecular biology
76. A Survey of Pretrained Protein Language Models
    Suresh Pokharel, Pawel Pratyush, Meenal Chaudhari, Michael Heinzinger, Doina Caragea, Hiroto Saigo, Dukka B. KC · 2025 · Methods in molecular biology
77. Exo-Tox: Identifying Exotoxins from secreted bacterial proteins
    Tanja Krueger, Damla Ayse Durmaz, Luisa F. Jiménez Soto · 2025 · BioData Mining
78. TmPred: Enhancing Thermophilic Protein Melting Point Prediction with Protein Language Models and Deep Learning
    Hao Jiang, Gongbo Zhang, Yuxiang Wang, Fengyi Jiang, Hongyu Zhang, Zhiwei Nie, Yuan Li, Jie Chen, Wenbin Zhang · 2025 · Chinese Journal of Polymer Science
79. Identifying microbial protease allergens through protein language model-guided homology
    Kumar Thurimella, Elena Wu, Chenhao Li, Daniel B. Graham, Róisı́n M. Owens, Damian Rafal Plichta, Caroline L. Sokol, Ramnik J. Xavier, Sergio Bacallado · 2026 · Cell Systems
80. Multi-view identification of key features affecting xylanase thermostability
    Shuyi Pan, L T Liu, Qunfang Yan, Yanbin Gu, Shiming Zhao, Yanrui Ding · 2026 · Computational Biology and Chemistry
81. CONTRA-IL6: an interpretable hybrid convolutional neural network and Transformer framework for accurate prediction of interleukin-6-inducing peptides using protein language models
    Duong Thanh Tran, Nhat Truong Pham, Gwang Lee, Shaherin Basith, Balachandran Manavalan · 2026 · Briefings in Bioinformatics
82. The role of protein embeddings for protein–protein interaction prediction with graph neural networks
    Laura Balbi, Rita T. Sousa, Pedro Giesteira Cotovio, Cátia Pesquita · 2026 · Briefings in Bioinformatics
83. AI-Driven Protein Research: From Prediction to Design
    Guodong Min, Huan Peng · 2026 · Methods in molecular biology
84. Optimizing protein tokenization: reduced amino acid alphabets for efficient and accurate protein language models
    Ella Rannon, David Burstein · 2026 · Bioinformatics
85. Seq2Pocket: augmenting protein language models for spatially consistent binding site prediction
    Vít Škrhák, Lukáš Polák, Marián Novotný, David Hoksza · 2026 · Bioinformatics
86. Deep sequence representation learning for predicting human proteins with liquid-liquid phase separation propensity and synaptic functions
    Anqi Wei, Liangjiang Wang · 2022 · ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB)
87. Sequence-Structure Embeddings via Protein Language Models Improve on Prediction Tasks
    Anowarul Kabir, Amarda Shehu · 2022 · IEEE International Conference on Knowledge Graph (ICKG)
88. BioSequence2Vec: Efficient Embedding Generation for Biological Sequences
    Sarwan Ali, Usama Sardar, Murray Patterson, Imdadullah Khan · 2023 · Lecture notes in computer science
89. PCD2Vec: A Poisson Correction Distance Based Approach for Viral Host Classification
    Sarwan Ali, Taslim Murad, Murray Patterson · 2023 · International Joint Conference on Neural Networks (IJCNN)
90. Word embeddings for protein sequence analysis
    Ana Marta Sequeira, Ivan Gomes, Miguel Rocha · 2023 · IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)
91. ResCNNT-fold: Combining residual convolutional neural network and Transformer for protein fold recognition from language model embeddings
    Xinyi Qin, Min Liu, Guangzhong Liu · 2023 · Computers in Biology and Medicine
92. Enhanced RNA Sequence Representation through Sequence Masking and Subsequence Consistency Optimization
    Yewei Shen, Zhiyuan Wang, Zongyu Li, Xinmeng Liu, Xuequn Shang, Yongtian Wang · 2023 · IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
93. How Much Do DNA and Protein Deep Embeddings Preserve Biological Information?
    Matteo Tolloso, Silvia Giulia Galfrè, Arianna Pavone, Marco Podda, Alina Sîrbu, Corrado Priami · 2024 · Lecture notes in computer science
94. The Effect of Multi-Task Learning on the Prediction of Neoantigen–MHC Class II Binding
    Kazuhiro Ikkyu, Itoshi Nikaido · 2025 · IEEE Transactions on Computational Biology and Bioinformatics
95. GPT2-ICC: A data-driven approach for accurate ion channel identification using pre-trained large language models
    Zihan Zhou, Yang Yu, Chengji Yang, Leyan Cao, Shaoying Zhang, Junnan Li, Yingnan Zhang, Huayun Han, Guoliang Shi, Qiansen Zhang et al. · 2025 · Journal of Pharmaceutical Analysis
96. Preserving Hidden Hierarchical Structure: Poincaré Distance for Enhanced Genomic Sequence Analysis
    Sarwan Ali, Haris Mansoor, Prakash Chourasia, Imdad Ulla Khan, Murray Patterson · 2025 · Communications in computer and information science
97. Nearest Neighbor CCP-Based Molecular Sequence Analysis
    Sarwan Ali, Prakash Chourasia, Bipin Koirala, Murray Patterson · 2025 · IEEE Transactions on Computational Biology and Bioinformatics
98. A Review of Protein Structure Prediction using Deep Learning
    Meredita Susanty, Tati Latifah Erawati Rajab, Rukman Hertadi · 2021 · BIO Web of Conferences
99. Application of Protein Language Models to low-N Engineering of metalloproteinase inhibitors
    Elham Khorasani Buxton, Rushabh Patel, Mari R. Toumaian, Maryam Raeeszadeh‐Sarmazdeh · 2021 · International Conference on Computational Science and Computational Intelligence (CSCI)
100. ProSE-Pero: Peroxisomal Protein Localization Identification Model Based on Self-Supervised Multi-Task Language Pre-Training Model
     Jianan Sui, Jiazi Chen, Yuehui Chen, Naoki Iwamori, Jin Sun · 2023 · Frontiers in Bioscience-Landmark