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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:

Machine Learning Guided Discovery of Non‐Hemolytic Membrane Disruptive Anticancer Peptides
E. Yu. Zakharova, Markus Orsi, Alice Capecchi, et al.
ChemMedChem (2022) Vol. 17, Iss. 17
Open Access | Times Cited: 26

Showing 1-25 of 26 citing articles:

Machine learning for antimicrobial peptide identification and design
Fangping Wan, Felix Wong, James J. Collins, et al.
Nature Reviews Bioengineering (2024) Vol. 2, Iss. 5, pp. 392-407
Closed Access | Times Cited: 52
The amphipathic design in helical antimicrobial peptides
Hai Bui Thi Phuong, Hoa Doan Ngan, Binh Le Huy, et al.
ChemMedChem (2024) Vol. 19, Iss. 7
Closed Access | Times Cited: 10
Structure-aware machine learning strategies for antimicrobial peptide discovery
Mariana del Carmen Aguilera‐Puga, Fabien Plisson
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 7
To Fold or Not to Fold: Diastereomeric Optimization of an α-Helical Antimicrobial Peptide
Hippolyte Personne, Thierry Paschoud, Sofia Fulgencio, et al.
Journal of Medicinal Chemistry (2023) Vol. 66, Iss. 11, pp. 7570-7583
Open Access | Times Cited: 15
Leveraging machine learning to streamline the development of liposomal drug delivery systems
Remo Eugster, Markus Orsi, Giorgio Buttitta, et al.
Journal of Controlled Release (2024) Vol. 376, pp. 1025-1038
Open Access | Times Cited: 5
Multi-dimensional deep learning drives efficient discovery of novel neuroprotective peptides from walnut protein isolates
Like Lin, Cong Li, Li Zhang, et al.
Food & Function (2023) Vol. 14, Iss. 15, pp. 6969-6984
Closed Access | Times Cited: 12
A breakthrough computational strategy for efficient enzymatic digestion of walnut protein to prepare antioxidant peptides
Like Lin, Dan Xiao, Wei Song, et al.
Food Chemistry (2025) Vol. 476, pp. 143311-143311
Closed Access
VIPER: Virus Inhibition Via Peptide Engineering and Receptor Mimicry
A Klingenberg, Dario Ghersi
Journal of Computational Biology (2025)
Closed Access
Antimicrobial Peptide–Peptoid Hybrids with and without Membrane Disruption
Etienne Bonvin, Hippolyte Personne, Thierry Paschoud, et al.
ACS Infectious Diseases (2023) Vol. 9, Iss. 12, pp. 2593-2606
Open Access | Times Cited: 9
Extracellular vesicles for developing targeted hearing loss therapy
Xiaoshu Pan, Yanjun Li, Peixin Huang, et al.
Journal of Controlled Release (2024) Vol. 366, pp. 460-478
Closed Access | Times Cited: 3
Integrating Traditional Machine Learning and Deep Learning for Precision Screening of Anticancer Peptides: A Novel Approach for Efficient Drug Discovery
M. Xu, Jiefu Pang, Yangyang Ye, et al.
ACS Omega (2024) Vol. 9, Iss. 14, pp. 16820-16831
Open Access | Times Cited: 3
Exploration of Rhenium Bisquinoline Tricarbonyl Complexes for their Antibacterial Properties
Sofia Fulgencio, Mirco Scaccaglia, Angelo Frei
ChemBioChem (2024) Vol. 25, Iss. 17
Open Access | Times Cited: 2
Impact of chemical modifications on the antimicrobial and hemolytic activity of helical amphipathic peptide Lasioglossin LL-III
Hai Bui Thi Phuong, Chi Le Uyen, Hoa Doan Ngan, et al.
Amino Acids (2023) Vol. 55, Iss. 11, pp. 1531-1544
Closed Access | Times Cited: 5
Benchmarking protein structure predictors to assist machine learning-guided peptide discovery
Victor Daniel Aldas-Bulos, Fabien Plisson
Digital Discovery (2023) Vol. 2, Iss. 4, pp. 981-993
Open Access | Times Cited: 4
Can Large Language Models Predict Antimicrobial Peptide Activity and Toxicity?
Markus Orsi, Jean‐Louis Reymond
(2024)
Open Access | Times Cited: 1
Exploration of Rhenium Bisquinoline Tricarbonyl Complexes for their Antibacterial Properties
Angelo Frei, Mirco Scaccaglia, Sofia Fulgencio
(2024)
Open Access | Times Cited: 1
Discovery of anticancer peptides from natural and generated sequences using deep learning
Jianda Yue, Tingting Li, Jiawei Xu, et al.
International Journal of Biological Macromolecules (2024) Vol. 290, pp. 138880-138880
Closed Access | Times Cited: 1
Can large language models predict antimicrobial peptide activity and toxicity?
Markus Orsi, Jean‐Louis Reymond
RSC Medicinal Chemistry (2024) Vol. 15, Iss. 6, pp. 2030-2036
Open Access | Times Cited: 1
Molecular Similarity for Drug Discovery, Target Prediction and Chemical Space Visualization
Jean‐Louis Reymond
CHIMIA International Journal for Chemistry (2022) Vol. 76, Iss. 12, pp. 1045-1045
Open Access | Times Cited: 6
An Active Machine Learning Discovery Platform for Membrane-Disrupting and Pore-forming Peptides.
Alexander van Teijlingen, Daniel C. Edwards, Liao Hu, et al.
Physical Chemistry Chemical Physics (2024) Vol. 26, Iss. 25, pp. 17745-17752
Open Access
Leveraging machine learning to streamline the development of liposomal drug delivery systems
Remo Eugster, Markus Orsi, Giorgio Buttitta, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Closed Access
Enhanced prediction of hemolytic activity in antimicrobial peptides using deep learning-based sequence analysis
Ibrahim Abdelbaky, Mohamed Elhakeem, Hilal Tayara, et al.
BMC Bioinformatics (2024) Vol. 25, Iss. 1
Open Access
GPT-3 accurately predicts antimicrobial peptide activity and hemolysis
Markus Orsi, Jean‐Louis Reymond
(2023)
Open Access | Times Cited: 1
Efficient Computational Framework for Target-Specific Active Peptide Discovery: A Case Study on IL-17C Targeting Cyclic Peptides
Zhipeng Wu, Yejian Wu, Zhu C, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 24, pp. 7655-7668
Closed Access | Times Cited: 1
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