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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 Prediction of Resistance to Subinhibitory Antimicrobial Concentrations from Escherichia coli Genomes
Sam Benkwitz-Bedford, Martin Palm, Talip Yasir Demirtas, et al.
mSystems (2021) Vol. 6, Iss. 4
Open Access | Times Cited: 11

Showing 11 citing articles:

Machine Learning for Antimicrobial Resistance Prediction: Current Practice, Limitations, and Clinical Perspective
Jee In Kim, Finlay Maguire, Kara K. Tsang, et al.
Clinical Microbiology Reviews (2022) Vol. 35, Iss. 3
Open Access | Times Cited: 82
Bacteria exposed to antiviral drugs develop antibiotic cross-resistance and unique resistance profiles
Veronica J. Wallace, Eric G. Sakowski, Sarah P. Preheim, et al.
Communications Biology (2023) Vol. 6, Iss. 1
Open Access | Times Cited: 18
Integrating whole genome sequencing and machine learning for predicting antimicrobial resistance in critical pathogens: a systematic review of antimicrobial susceptibility tests
Carlos M. Ardila, Pradeep Kumar Yadalam, Daniel González‐Arroyave
PeerJ (2024) Vol. 12, pp. e18213-e18213
Open Access | Times Cited: 1
Genome-Wide Association Study Reveals Host Factors Affecting Conjugation in Escherichia coli
Laetitia Van Wonterghem, Matteo De Chiara, Gianni Liti, et al.
Microorganisms (2022) Vol. 10, Iss. 3, pp. 608-608
Open Access | Times Cited: 5
Predictive modeling of antibiotic eradication therapy success for new-onset Pseudomonas aeruginosa pulmonary infections in children with cystic fibrosis
Lucía Graña-Miraglia, Nadia Morales-Lizcano, Pauline W. Wang, et al.
PLoS Computational Biology (2023) Vol. 19, Iss. 9, pp. e1011424-e1011424
Open Access | Times Cited: 2
An Automated Machine Learning Framework for Antimicrobial Resistance Prediction Through Transcriptomics
Adil Alsiyabi, Syed Ahsan Shahid, Ahmed Al‐Harrasi
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Closed Access
Identification of key drivers of antimicrobial resistance in Enterococcus using machine learning
Jee In Kim, Alexander Manuele, Finlay Maguire, et al.
Canadian Journal of Microbiology (2024) Vol. 70, Iss. 10, pp. 446-460
Closed Access
Applications of Artificial Intelligence and Machine Learning in Antimicrobial Resistance Study
A. Durga Praveen, Nicholas Bartelo, Vijay Soni
Springer eBooks (2024), pp. 359-385
Closed Access
Plasmid permissiveness of wastewater microbiomes can be predicted from 16S rRNA sequences by machine learning
Danesh Moradigaravand, Liguan Li, Arnaud Dechesne, et al.
Bioinformatics (2023) Vol. 39, Iss. 7
Open Access | Times Cited: 1
Plasmid Permissiveness of Wastewater Microbiomes can be Predicted from 16S rDNA sequences by Machine Learning
Danesh Moradigaravand, Liguan Li, Arnaud Dechesne, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 1
Predictive modeling of antibiotic eradication therapy success for new-onsetPseudomonas aeruginosapulmonary infections in children with cystic fibrosis
Lucía Graña-Miraglia, Nadia Morales-Lizcano, Pauline W. Wang, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access
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