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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:

A hybrid model combining evolutionary probability and machine learning leverages data-driven protein engineering
Alexander-Maurice Illig, Niklas E. Siedhoff, Ulrich Schwaneberg, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 9

Showing 9 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
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
Biophysics-based protein language models for protein engineering
Sam Gelman, Bryce Johnson, Chase R. Freschlin, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 9
Learning Epistasis and Residue Coevolution Patterns: Current Trends and Future Perspectives for Advancing Enzyme Engineering
Marcel Wittmund, Frédéric Cadet, Mehdi D. Davari
ACS Catalysis (2022) Vol. 12, Iss. 22, pp. 14243-14263
Closed Access | Times Cited: 33
Addressing data scarcity in protein fitness landscape analysis: A study on semi-supervised and deep transfer learning techniques
José A. Barbero‐Aparicio, Alicia Olivares‐Gil, Juan J. Rodríguez, et al.
Information Fusion (2023) Vol. 102, pp. 102035-102035
Open Access | Times Cited: 15
An interpretable composite CNN and GRU for fine-grained martial arts motion modeling using big data analytics and machine learning
Gang Chen
Soft Computing (2024) Vol. 28, Iss. 3, pp. 2223-2243
Closed Access | Times Cited: 2
Interpretable and explainable predictive machine learning models for data-driven protein engineering
David Medina-Ortiz, Ashkan Khalifeh, Hoda Anvari-Kazemabad, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1
Engineering of Substrate Tunnel of P450 CYP116B3 though Machine Learning
Yiheng Liu, Zhongyu Li, Chenqi Cao, et al.
Catalysts (2023) Vol. 13, Iss. 8, pp. 1228-1228
Open Access | Times Cited: 3
Machine Learning-Assisted Engineering of Light, Oxygen, Voltage Photoreceptor Adduct Lifetime
Stefanie Hemmer, Niklas E. Siedhoff, Sophia Werner, et al.
JACS Au (2023) Vol. 3, Iss. 12, pp. 3311-3323
Open Access | Times Cited: 2
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