Cited by 695Antibiotic Resistance in BacteriaAntibiotic Use and ResistanceBacterial Identification and Susceptibility Testing

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

ResFinder–an open online resource for identification of antimicrobial resistance genes in next-generation sequencing data and prediction of phenotypes from genotypes

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Abstract

Antimicrobial resistance (AMR) is one of the most important health threats globally. The ability to accurately identify resistant bacterial isolates and the individual antimicrobial resistance genes (ARGs) is essential for understanding the evolution and emergence of AMR and to provide appropriate treatment. The rapid developments in next-generation sequencing technologies have made this technology available to researchers and microbiologists at routine laboratories around the world. However, tools available for those with limited experience with bioinformatics are lacking, especially to enable researchers and microbiologists in low- and middle-income countries (LMICs) to perform their own studies. The CGE-tools (Center for Genomic Epidemiology) including ResFinder ( https://cge.cbs.dtu.dk/services/ResFinder/ ) was developed to provide freely available easy to use online bioinformatic tools allowing inexperienced researchers and microbiologists to perform simple bioinformatic analyses. The main purpose was and is to provide these solutions for people involved in frontline diagnosis especially in LMICs. Since its original publication in 2012, ResFinder has undergone a number of improvements including improvement of the code and databases, inclusion of point mutations for selected bacterial species and predictions of phenotypes also for selected species. As of 28 September 2021, 820 803 analyses have been performed using ResFinder from 61 776 IP-addresses in 171 countries. ResFinder clearly fulfills a need for several people around the globe and we hope to be able to continue to provide this service free of charge in the future. We also hope and expect to provide further improvements including phenotypic predictions for additional bacterial species.

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  • Computational approaches are primarily used in early stages of discovery and safety screening to identify potential antibiotic resistance genes, virulence-associated traits, and mobile genetic elements, enabling risk assessment and regulatory evaluation.

    “These approaches are primarily used in the early stages of discovery and safety screening to identify potential antibiotic resistance genes, virulence-associated traits, and mobile genetic elements, enabling risk assessment and regulatory evaluation, and supporting phenotypic analyses and clinical validation [31,152,153].”

    From Current Concepts in Probiotic Safety and Efficacy (2026) · cites this paper as [152]

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  • CARD and ResFinder use carefully curated databases to identify known antibiotic resistance genes, providing clear results but may fail to detect novel, unusual, or modulated resistance mechanisms.

    “In contrast, CARD and ResFinder use carefully curated databases to identify known antibiotic resistance genes, providing clear results but may fail to detect novel, unusual, or modulated resistance mechanisms [67,152,167,168].”

    From Current Concepts in Probiotic Safety and Efficacy (2026) · cites this paper as [152]

    The Development sections describe ResFinder’s manually curated database of known resistance genes and say its rule-based predictions depend on prior knowledge, limiting accuracy for less-studied resistance mechanisms (page numbers unavailable). The paper does not establish that CARD is carefully curated or specifically discuss failure to detect unusual or modulated mechanisms. (LLM, conf=0.84)

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Metadata

Authors
Florensa, A. F., Kaas, R. S., Clausen, P. T. L. C., Aytan-Aktug, D., & Aarestrup, F. M.
Affiliations
Technical University of Denmark (DK)
Corresponding author
Aarestrup, Frank M.
Venue
Microbial Genomics
Published
2022-01-17
Volume
8
Issue
1
ISSN
2057-5858 (ISSN-L)
OpenAlex
W4207067711
Cited by
695
References
1
Citations by year
2026: 161 · 2025: 196 · 2024: 195 · 2023: 116 · 2022: 27
FWCI
43.82
Type
journal article
Language
en
Open access
Locations
  • Microbial Genomics (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (submittedVersion, cc-by)
Funders
  • Novo Nordisk Fonden (NNF16OC0021856)
  • H2020 Societal Challenges (874735)
Topics
  • Health Sciences › Medicine › Microbiology (medical) › Antibiotic Resistance in Bacteria
  • Health Sciences › Medicine › Infectious Diseases › Antibiotic Use and Resistance
  • Health Sciences › Medicine › Microbiology (medical) › Bacterial Identification and Susceptibility Testing
Keywords
ResFinder, antimicrobial resistance genes, antimicrobial resistance, online bioinformatics tools, genotype-phenotype prediction, point mutations, low- and middle-income countries, bacterial isolates, resistance gene detection
MeSH terms
Bacteria, Bacterial Proteins, Microbial Sensitivity Tests, Mutation, Phenotype, Software, Genome, Bacterial, Sequence Analysis, DNA, Computational Biology, Internet, Drug Resistance, Bacterial, Databases, Genetic, High-Throughput Nucleotide Sequencing

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