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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Self-play reinforcement learning guides protein engineering
Yi Wang, Hui Tang, Lichao Huang, et al.
Nature Machine Intelligence (2023) Vol. 5, Iss. 8, pp. 845-860
Closed Access | Times Cited: 31

Showing 1-25 of 31 citing articles:

Machine Learning-Guided Protein Engineering
Petr Kouba, Pavel Kohout, Faraneh Haddadi, et al.
ACS Catalysis (2023) Vol. 13, Iss. 21, pp. 13863-13895
Open Access | Times Cited: 65
Design of intrinsically disordered protein variants with diverse structural properties
Francesco Pesce, Anne Bremer, Giulio Tesei, et al.
Science Advances (2024) Vol. 10, Iss. 35
Open Access | Times Cited: 10
Deep learning for advancing peptide drug development: Tools and methods in structure prediction and design
Xinyi Wu, Huitian Lin, Renren Bai, et al.
European Journal of Medicinal Chemistry (2024) Vol. 268, pp. 116262-116262
Closed Access | Times Cited: 8
Data and AI-driven synthetic binding protein discovery
Yanlin Li, Zixin Duan, Zhenwen Li, et al.
Trends in Pharmacological Sciences (2025)
Closed Access
Painting Peptides with Antimicrobial Potency through Deep Reinforcement Learning
Ruihan Dong, Qiushi Cao, Chen Song
bioRxiv (Cold Spring Harbor Laboratory) (2025)
Open Access
Artificial intelligence in peptide-based drug design
Silong Zhai, Tiantao Liu, Shaolong Lin, et al.
Drug Discovery Today (2025), pp. 104300-104300
Closed Access
On synergy between ultrahigh throughput screening and machine learning in biocatalyst engineering
Maximilian Gantz, Simon V. Mathis, Friederike E. H. Nintzel, et al.
Faraday Discussions (2024) Vol. 252, pp. 89-114
Open Access | Times Cited: 4
Design of linear and cyclic peptide binders of different lengths only from a protein target sequence
Q. Li, Efstathios Nikolaos Vlachos, Patrick Bryant
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 4
EITLEM-Kinetics: A deep-learning framework for kinetic parameter prediction of mutant enzymes
Xiaowei Shen, Ziheng Cui, Jianyu Long, et al.
Chem Catalysis (2024) Vol. 4, Iss. 9, pp. 101094-101094
Closed Access | Times Cited: 4
Deep Learning-Assisted Spectrum–Structure Correlation: State-of-the-Art and Perspectives
Xinyu Lu, Hao-Ping Wu, Hao Ma, et al.
Analytical Chemistry (2024) Vol. 96, Iss. 20, pp. 7959-7975
Closed Access | Times Cited: 3
An intelligent approach: Integrating ChatGPT for experiment planning in biochar immobilization of soil cadmium
Hongwei Yang, Jie Wang, Rumeng Mo, et al.
Separation and Purification Technology (2024) Vol. 352, pp. 128170-128170
Closed Access | Times Cited: 3
Int&in: A machine learning‐based web server for active split site identification in inteins
Mirko Schmitz, Jara Ballestin Ballestin, Junsheng Liang, et al.
Protein Science (2024) Vol. 33, Iss. 6
Open Access | Times Cited: 2
From predicting to decision making: Reinforcement learning in biomedicine
Xuhan Liu, Jun Zhang, Zhonghuai Hou, et al.
Wiley Interdisciplinary Reviews Computational Molecular Science (2024) Vol. 14, Iss. 4
Closed Access | Times Cited: 2
Growing ecosystem of deep learning methods for modeling protein–protein interactions
Julia R. Rogers, Gergő Nikolényi, Mohammed AlQuraishi
Protein Engineering Design and Selection (2023) Vol. 36
Open Access | Times Cited: 5
Design of intrinsically disordered protein variants with diverse structural properties
Francesco Pesce, Anne Bremer, Giulio Tesei, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 5
Integrating Reinforcement Learning and Monte Carlo Tree Search for enhanced neoantigen vaccine design
Yicheng Lin, Jiakang Ma, Haozhe Yuan, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 3
Open Access | Times Cited: 1
Advancing microbial production through artificial intelligence-aided biology
Xinyu Gong, Jianli Zhang, Qi Gan, et al.
Biotechnology Advances (2024) Vol. 74, pp. 108399-108399
Closed Access | Times Cited: 1
Interpretable and explainable predictive machine learning models for data-driven protein engineering
David Medina-Ortiz, Ashkan Khalifeh, Hoda Anvari-Kazemabad, et al.
Biotechnology Advances (2024) Vol. 79, pp. 108495-108495
Open Access | Times Cited: 1
An Intelligent Approach: Integrating Openai for Experiment Planning in Biochar Immobilization of Soil Cd
Hongwei Yang, Jie Wang, Rumeng Mo, et al.
(2024)
Closed Access
An efficient and lightweight off-policy actor-critic reinforcement learning framework
Huaqing Zhang, Hongbin Ma, Xiaofei Zhang, et al.
Applied Soft Computing (2024) Vol. 163, pp. 111814-111814
Closed Access
Multi-Modal CLIP-Informed Protein Editing
Mingze Yin, Hanjing Zhou, Yiheng Zhu, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Artificial design of the genome: from sequences to the 3D structure of chromosomes
Junyi Wang, Ze‐Xiong Xie, You‐Zhi Cui, et al.
Trends in biotechnology (2024)
Closed Access
Deep Reinforcement Learning in Healthcare and Biomedical Research
Shruti Agrawal, Pralay Mitra
(2024), pp. 179-205
Closed Access
Variation and evolution analysis of SARS-CoV-2 using self-game sequence optimization
Ziyu Liu, Yi Shen, Yunliang Jiang, et al.
Frontiers in Microbiology (2024) Vol. 15
Open Access
Multi-Modal CLIP-Informed Protein Editing
Mingze Yin, Hanjing Zhou, Yiheng Zhu, et al.
Health Data Science (2024) Vol. 4
Open Access
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