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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 and deep learning meet genome-scale metabolic modeling
Guido Zampieri, Supreeta Vijayakumar, Elisabeth Yaneske, et al.
PLoS Computational Biology (2019) Vol. 15, Iss. 7, pp. e1007084-e1007084
Open Access | Times Cited: 246

Showing 1-25 of 246 citing articles:

Common principles and best practices for engineering microbiomes
Christopher E. Lawson, William R. Harcombe, Roland Hatzenpichler, et al.
Nature Reviews Microbiology (2019) Vol. 17, Iss. 12, pp. 725-741
Open Access | Times Cited: 438
Machine learning for precision medicine
Sarah J. MacEachern, Nils D. Forkert
Genome (2020) Vol. 64, Iss. 4, pp. 416-425
Closed Access | Times Cited: 293
A survey on deep learning in medicine: Why, how and when?
Francesco Piccialli, Vittorio Di Somma, Fabio Giampaolo, et al.
Information Fusion (2020) Vol. 66, pp. 111-137
Closed Access | Times Cited: 280
Machine Learning Applications for Mass Spectrometry-Based Metabolomics
Ulf W. Liebal, An Phan, Malvika Sudhakar, et al.
Metabolites (2020) Vol. 10, Iss. 6, pp. 243-243
Open Access | Times Cited: 250
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
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
Biological network analysis with deep learning
Giulia Muzio, Leslie O’Bray, Karsten Borgwardt
Briefings in Bioinformatics (2020) Vol. 22, Iss. 2, pp. 1515-1530
Open Access | Times Cited: 170
Machine learning applications in systems metabolic engineering
Gi Bae Kim, Won Jun Kim, Hyun Uk Kim, et al.
Current Opinion in Biotechnology (2019) Vol. 64, pp. 1-9
Closed Access | Times Cited: 142
Deep learning for plant genomics and crop improvement
Wang Hai, Emre Çimen, Nisha Singh, et al.
Current Opinion in Plant Biology (2020) Vol. 54, pp. 34-41
Open Access | Times Cited: 142
Deep Learning for Smart Healthcare—A Survey on Brain Tumor Detection from Medical Imaging
Mahsa Arabahmadi, Reza Farahbakhsh, Javad Rezazadeh
Sensors (2022) Vol. 22, Iss. 5, pp. 1960-1960
Open Access | Times Cited: 133
Integration of machine learning and genome-scale metabolic modeling identifies multi-omics biomarkers for radiation resistance
Joshua E. Lewis, Melissa L. Kemp
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 132
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
Using machine learning as a surrogate model for agent-based simulations
Claudio Angione, Eric Silverman, Elisabeth Yaneske
PLoS ONE (2022) Vol. 17, Iss. 2, pp. e0263150-e0263150
Open Access | Times Cited: 67
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
The interplay between diet and the gut microbiome: implications for health and disease
Fiona C. Ross, Dhrati Patangia, Ghjuvan Micaelu Grimaud, et al.
Nature Reviews Microbiology (2024) Vol. 22, Iss. 11, pp. 671-686
Closed Access | Times Cited: 55
Machine learning applications in stroke medicine: advancements, challenges, and future prospectives
Mario Daidone, Sergio Ferrantelli, Antonino Tuttolomondo
Neural Regeneration Research (2023) Vol. 19, Iss. 4, pp. 769-773
Open Access | Times Cited: 43
Unlocking the magic in mycelium: Using synthetic biology to optimize filamentous fungi for biomanufacturing and sustainability
Charles Jo, Jing Zhang, Jenny M. Tam, et al.
Materials Today Bio (2023) Vol. 19, pp. 100560-100560
Open Access | Times Cited: 40
Engineering strategies for enhanced heterologous protein production by Saccharomyces cerevisiae
Meirong Zhao, Jianfan Ma, Lei Zhang, et al.
Microbial Cell Factories (2024) Vol. 23, Iss. 1
Open Access | Times Cited: 15
Biosystems Design by Machine Learning
Michael Volk, Ismini Lourentzou, Shekhar Mishra, et al.
ACS Synthetic Biology (2020) Vol. 9, Iss. 7, pp. 1514-1533
Closed Access | Times Cited: 104
Multiview learning for understanding functional multiomics
Nam D. Nguyen, Daifeng Wang
PLoS Computational Biology (2020) Vol. 16, Iss. 4, pp. e1007677-e1007677
Open Access | Times Cited: 91
Deep learning meets metabolomics: a methodological perspective
Partho Sen, Santosh Lamichhane, Vivek Bhakta Mathema, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 2, pp. 1531-1542
Closed Access | Times Cited: 88
Metabolic modelling approaches for describing and engineering microbial communities
Beatriz García-Jiménez, Jesús Torres‐Bacete, Juan Nogales
Computational and Structural Biotechnology Journal (2020) Vol. 19, pp. 226-246
Open Access | Times Cited: 76
A mechanism-aware and multiomic machine-learning pipeline characterizes yeast cell growth
Christopher Culley, Supreeta Vijayakumar, Guido Zampieri, et al.
Proceedings of the National Academy of Sciences (2020) Vol. 117, Iss. 31, pp. 18869-18879
Open Access | Times Cited: 74
Metabolomics and complementary techniques to investigate the plant phytochemical cosmos
Hiroshi Tsugawa, Amit Rai, Kazuki Saito, et al.
Natural Product Reports (2021) Vol. 38, Iss. 10, pp. 1729-1759
Open Access | Times Cited: 71
AI applications in functional genomics
Claudia Caudai, Antonella Galizia, Filippo Geraci, et al.
Computational and Structural Biotechnology Journal (2021) Vol. 19, pp. 5762-5790
Open Access | Times Cited: 70
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