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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 machine learning Automated Recommendation Tool for synthetic biology
Tijana Radivojević, Zak Costello, Kenneth Workman, et al.
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 193

Showing 1-25 of 193 citing articles:

Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism
Jie Zhang, Søren D. Petersen, Tijana Radivojević, et al.
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 201
Microbial production of advanced biofuels
Jay D. Keasling, Héctor García Martín, Taek Soon Lee, et al.
Nature Reviews Microbiology (2021) Vol. 19, Iss. 11, pp. 701-715
Open Access | Times Cited: 200
Machine learning for metabolic engineering: A review
Christopher E. Lawson, Jose Manuel Martí, Tijana Radivojević, et al.
Metabolic Engineering (2020) Vol. 63, pp. 34-60
Open Access | Times Cited: 198
Design of synthetic human gut microbiome assembly and butyrate production
Ryan L. Clark, Bryce Connors, David Stevenson, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 135
Metabolic Engineering: Methodologies and Applications
Michael Volk, Vinh Tran, Shih‐I Tan, et al.
Chemical Reviews (2022) Vol. 123, Iss. 9, pp. 5521-5570
Closed Access | Times Cited: 86
A versatile active learning workflow for optimization of genetic and metabolic networks
Amir Pandi, Christoph Diehl, Ali Yazdizadeh Kharrazi, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 70
Machine learning-enabled retrobiosynthesis of molecules
Tianhao Yu, Aashutosh Girish Boob, Michael Volk, et al.
Nature Catalysis (2023) Vol. 6, Iss. 2, pp. 137-151
Closed Access | Times Cited: 62
Big data and machine learning driven bioprocessing – Recent trends and critical analysis
Chao‐Tung Yang, Endah Kristiani, Yoong Kit Leong, et al.
Bioresource Technology (2023) Vol. 372, pp. 128625-128625
Closed Access | Times Cited: 39
Revolutionizing agriculture with artificial intelligence: plant disease detection methods, applications, and their limitations
Abbas Jafar, N. Bibi, Rizwan Ali Naqvi, et al.
Frontiers in Plant Science (2024) Vol. 15
Open Access | Times Cited: 36
Machine Learning and Deep Learning in Synthetic Biology: Key Architectures, Applications, and Challenges
Manoj Kumar Goshisht
ACS Omega (2024) Vol. 9, Iss. 9, pp. 9921-9945
Open Access | Times Cited: 20
Relieving metabolic burden to improve robustness and bioproduction by industrial microorganisms
Jiwei Mao, Hongyu Zhang, Yu Chen, et al.
Biotechnology Advances (2024) Vol. 74, pp. 108401-108401
Open Access | Times Cited: 15
The forefront of chemical engineering research
Laura Torrente‐Murciano, Jennifer B. Dunn, Panagiotis D. Christofides, et al.
Nature Chemical Engineering (2024) Vol. 1, Iss. 1, pp. 18-27
Open Access | Times Cited: 13
Synthetic biology in the clinic: engineering vaccines, diagnostics, and therapeutics
Xiao Tan, Justin H. Letendre, James J. Collins, et al.
Cell (2021) Vol. 184, Iss. 4, pp. 881-898
Open Access | Times Cited: 86
Vision, challenges and opportunities for a Plant Cell Atlas
Jahed Ahmed, Oluwafemi Alaba, Gazala Ameen, et al.
eLife (2021) Vol. 10
Open Access | Times Cited: 63
Sensing the future of bio-informational engineering
Thomas A. Dixon, Thomas C. Williams, Isak S. Pretorius
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 58
Knowledge graph-based recommendation framework identifies drivers of resistance in EGFR mutant non-small cell lung cancer
Anna Gogleva, Dimitris Polychronopoulos, Matthias Pfeifer, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 57
Machine learning in bioprocess development: from promise to practice
Laura M. Helleckes, Johannes Hemmerich, Wolfgang Wiechert, et al.
Trends in biotechnology (2022) Vol. 41, Iss. 6, pp. 817-835
Open Access | Times Cited: 55
Recent advances in machine learning applications in metabolic engineering
Pradipta Patra, Disha B.R., Pritam Kundu, et al.
Biotechnology Advances (2022) Vol. 62, pp. 108069-108069
Closed Access | Times Cited: 44
Comparison of machine learning methods for predicting the methane production from anaerobic digestion of lignocellulosic biomass
Zheng‐Xin Wang, Xinggan Peng, Ao Xia, et al.
Energy (2022) Vol. 263, pp. 125883-125883
Closed Access | Times Cited: 43
Enabling technology and core theory of synthetic biology
Xian‐En Zhang, Chenli Liu, Junbiao Dai, et al.
Science China Life Sciences (2023) Vol. 66, Iss. 8, pp. 1742-1785
Open Access | Times Cited: 30
Generative Artificial Intelligence GPT-4 Accelerates Knowledge Mining and Machine Learning for Synthetic Biology
Zhengyang Xiao, Wenyu Li, Hannah Moon, et al.
ACS Synthetic Biology (2023) Vol. 12, Iss. 10, pp. 2973-2982
Open Access | Times Cited: 27
Integration of graph neural networks and genome-scale metabolic models for predicting gene essentiality
Ramin Hasibi, Tom Michoel, Diego A. Oyarzún
npj Systems Biology and Applications (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 9
Revisiting Solar Energy Flow in Nanomaterial-Microorganism Hybrid Systems
Jun Liang, Kemeng Xiao, Xinyu Wang, et al.
Chemical Reviews (2024) Vol. 124, Iss. 15, pp. 9081-9112
Closed Access | Times Cited: 8
Neural network extrapolation to distant regions of the protein fitness landscape
Chase R. Freschlin, Sarah A. Fahlberg, Pete Heinzelman, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 8
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