The DOI matches its Crossref record; 166 of the 166 references it cites were found in a registry or an index.
Advances in Chemical and Biological Methods to Identify Microorganisms—From Past to Present
Open accessAbstract
Fast detection and identification of microorganisms is a challenging and significant feature from industry to medicine. Standard approaches are known to be very time-consuming and labor-intensive (e.g., culture media and biochemical tests). Conversely, screening techniques demand a quick and low-cost grouping of bacterial/fungal isolates and current analysis call for broad reports of microorganisms, involving the application of molecular techniques (e.g., 16S ribosomal RNA gene sequencing based on polymerase chain reaction). The goal of this review is to present the past and the present methods of detection and identification of microorganisms, and to discuss their advantages and their limitations.
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.
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
Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics
White, T. J., Bruns, T., Lee, S., & Taylor, J. (1990) · PCR Protocols · doi:10.1016/b978-0-12-372180-8.50042-1 · Cited by 36,648
The origins and the future of microfluidics
Whitesides, G. M. (2006) · Nature · doi:10.1038/nature05058 · Cited by 9,687
Mass spectrometry‐based metabolomics
Dettmer, K., Aronov, P. A., & Hammock, B. D. (2007) · Mass Spectrometry Reviews · doi:10.1002/mas.20108 · Cited by 2,241
Antimicrobial Susceptibility Testing: A Review of General Principles and Contemporary Practices
Jorgensen, J. H., & Ferraro, M. J. (2009) · Clinical Infectious Diseases · doi:10.1086/647952 · Cited by 1,894
Molecular Identification of Bacteria Associated with Bacterial Vaginosis
Fredricks, D. N., Fiedler, T. L., & Marrazzo, J. M. (2005) · New England Journal of Medicine · doi:10.1056/nejmoa043802 · Cited by 1,303
Kind, T., & Fiehn, O. (2007) · BMC Bioinformatics · doi:10.1186/1471-2105-8-105 · Cited by 1,201
Metabolomics: Current analytical platforms and methodologies
(2005) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2004.11.021 · Cited by 1,192
Use of SYBR Green I for rapid epifluorescence counts of marine viruses and bacteria
Noble, R., & Fuhrman, J. (1998) · Aquatic Microbial Ecology · doi:10.3354/ame014113 · Cited by 974
Lagier, J.-C., Hugon, P., Khelaifia, S., Fournier, P.-E., La Scola, B., & Raoult, D. (2015) · Clinical Microbiology Reviews · doi:10.1128/cmr.00014-14 · Cited by 831
Amann, R., & Fuchs, B. M. (2008) · Nature Reviews Microbiology · doi:10.1038/nrmicro1888 · Cited by 768
Cited by
Han, X., Liu, Q., Li, Y., Zhang, M., Liu, K., Kwok, L.-Y., Zhang, H., & Zhang, W. (2025) · Trends in Food Science & Technology · doi:10.1016/j.tifs.2025.104938 · Cited by 64
BioTransformer 4.0 a comprehensive computational tool for small molecule metabolism prediction
Tian, S., Feunang, Y. D., Oler, E., Wang, F., Greiner, R., Palm, E. H., Schymanski, E. L., Manach, C., & Wishart, D. S. (2025) · doi:10.1101/2025.07.28.667289 · Cited by 5
“Traditional metabolite identification typically involves exploring plausible metabolite structures both theoretically and experimentally, which is time-consuming, expensive, and often incomplete [6].”
Microbe Detectives VS ChatGPT: Who Solves Better
Aguirre, A. H. (2024) · 2024 World Engineering Education Forum - Global Engineering Deans Council (WEEF-GEDC) · doi:10.1109/weef-gedc63419.2024.10854897 · Cited by 1
Metadata
- Authors
- Franco-Duarte, R., Černáková, L., Kadam, S., S. Kaushik, K., Salehi, B., Bevilacqua, A., Corbo, M. R., Antolak, H., Dybka-Stępień, K., Leszczewicz, M., Relison Tintino, S., Alexandrino de Souza, V. C., Sharifi-Rad, J., Melo Coutinho, H. D., Martins, N., & Rodrigues, C. F.
- Venue
- Microorganisms
- Publisher
- MDPI AG
- Published
- 2019-05-13
- Volume
- 7
- Issue
- 5
- Pages
- 130
- ISSN
- 2076-2607 (ISSN-L)
- OpenAlex
- W2946281629
- Cited by
- 565
- References
- 166
- FWCI
- 24.15
- Type
- journal article
- Language
- en
- Open access
- gold
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Advances in Chemical and Biological Methods to Identify Microorganisms—From Past to Present. https://app.cochat.ai/papers/10.3390/microorganisms7050130
- The paper
- Franco-Duarte, R., Černáková, L., Kadam, S., S. Kaushik, K., Salehi, B., Bevilacqua, A., Corbo, M. R., Antolak, H., Dybka-Stępień, K., Leszczewicz, M., Relison Tintino, S., Alexandrino de Souza, V. C., Sharifi-Rad, J., Melo Coutinho, H. D., Martins, N., & Rodrigues, C. F. (2019). Advances in Chemical and Biological Methods to Identify Microorganisms—From Past to Present. Microorganisms. https://doi.org/10.3390/microorganisms7050130
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
