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
Open accessAbstract
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
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]
Split into 2 atoms — 0 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 1 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measuredCARD 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)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
BLAST+: architecture and applications
Camacho, C., Coulouris, G., Avagyan, V., Ma, N., Papadopoulos, J., Bealer, K., & Madden, T. L. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-421 · Cited by 22,074
Flagged first, then by citations
Research works printed but not linked: 39
- 10.1596/32552 · DOI
- 10.1016/j.vetmic.2005.12.016 · DOI
- 10.1128/JCM.00894-08 · DOI
- 10.1128/JCM.01066-18 · DOI
- 10.1016/j.cmi.2016.11.012 · DOI · Paper page
- 10.3389/fpubh.2019.00242 · DOI
- 10.1093/jac/dks496 · DOI
- 10.1093/jac/dkt180 · DOI
- 10.1093/jac/dkv186 · DOI
- 10.1128/AEM.02873-15 · DOI
- 10.1128/AAC.01030-16 · DOI
- 10.1093/jac/dkz055 · DOI
- 10.3389/fmicb.2019.02464 · DOI
- 10.1128/JCM.06094-11 · DOI
- 10.1128/JCM.02981-13 · DOI
- 10.1128/AAC.02412-14 · DOI · Paper page
- 10.1371/journal.pone.0104984 · DOI
- 10.1128/mSphere.00612-17 · DOI
- 10.1093/jac/dks261 · DOI · Paper page
- 10.1093/jac/dkaa345 · DOI · Paper page
- 10.3201/eid1305.061489 · DOI
- 10.1089/fpd.2010.0787 · DOI
- 10.3201/eid/1811.120453 · DOI
- 10.1016/j.tim.2016.01.009 · DOI
- 10.1128/AAC.00419-13 · DOI
- 10.1093/jac/dkx217 · DOI
- 10.1101/gr.074492.107 · DOI
- 10.1089/cmb.2012.0021 · DOI
- 10.1186/s13073-014-0090-6 · DOI
- 10.1093/jac/dkw184 · DOI
- 10.1186/s12859-018-2336-6 · DOI
- 10.1093/jac/dkz092 · DOI
- 10.1111/hel.12752 · DOI
- 10.1128/mSystems.00774-19 · DOI
- 10.1038/s41598-020-71693-5 · DOI
- 10.1128/mSystems.00185-21 · DOI
- 10.1038/s41598-017-18972-w · DOI
- 10.1128/JCM.01260-18 · DOI
- 10.1038/s41467-018-06634-y · DOI
Cited by
Sorted by citations
Current Concepts in Probiotic Safety and Efficacy
Churin, A. A., Sokolyanskaya, L. O., Lukina, A. P., & Karnachuk, O. V. (2026) · Nutrients · doi:10.3390/nu18040696 · Cited by 31
Di Pierro, F., Sagheddu, V., Galletti, S., Casaroli, A., Labrini, E., Soldi, S., Cazzaniga, M., Bertuccioli, A., Matera, M., Cavecchia, I., et al. (2026) · Probiotics and Antimicrobial Proteins · doi:10.1007/s12602-025-10522-5 · Cited by 5
“The presence of putative AMR genes was ascertained using ABRicate [82] against the following databases: NCBI AMRFinderPlus [83], CARD [84], Resfinder [85], ARG-ANNOT [86], MEGARES [87], and EcOH [88].”
Sliti, A., Kim, R.-H., Lee, D., & Shin, J.-H. (2025) · Microbial Pathogenesis · doi:10.1016/j.micpath.2025.107405 · Cited by 5
Arnoux, J. (2026) · Thèse de doctorat, Université Paris-Saclay / PPanGGOLiN · doi:10.70675/eee354d9zf63dz48ebz9444zd1809f8fb74d
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.
- ORCID
- Venue
- Microbial Genomics
- Publisher
- Microbiology Society
- Published
- 2022-01-17
- Volume
- 8
- Issue
- 1
- ISSN
- 2057-5858 (ISSN-L)
- PMC
- PMC8914360
- 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
- gold
- doi.org
- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review