The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
DNA barcoding the floras of biodiversity hotspots
Open accessAbstract
DNA barcoding is a technique in which species identification is performed by using DNA sequences from a small fragment of the genome, with the aim of contributing to a wide range of ecological and conservation studies in which traditional taxonomic identification is not practical. DNA barcoding is well established in animals, but there is not yet any universally accepted barcode for plants. Here, we undertook intensive field collections in two biodiversity hotspots (Mesoamerica and southern Africa). Using >1,600 samples, we compared eight potential barcodes. Going beyond previous plant studies, we assessed to what extent a “DNA barcoding gap” is present between intra- and interspecific variations, using multiple accessions per species. Given its adequate rate of variation, easy amplification, and alignment, we identified a portion of the plastid matK gene as a universal DNA barcode for flowering plants. Critically, we further demonstrate the applicability of DNA barcoding for biodiversity inventories. In addition, analyzing >1,000 species of Mesoamerican orchids, DNA barcoding with matK alone reveals cryptic species and proves useful in identifying species listed in Convention on International Trade of Endangered Species (CITES) appendixes.
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
Biodiversity hotspots for conservation priorities
Myers, N., Mittermeier, R. A., Mittermeier, C. G., da Fonseca, G. A. B., & Kent, J. (2000) · Nature · doi:10.1038/35002501 · Cited by 31,710
DNA barcoding: error rates based on comprehensive sampling
Meyer, C. P., & Paulay, G. (2005) · PLoS Biology · doi:10.1371/journal.pbio.0030422 · Cited by 1,957
Cited by
The application of biotechnology to orchids
Hossain, M. M., Kant, R., Van, P. T., Winarto, B., Zeng, S., & Teixeira da Silva, J. A. (2013) · Critical Reviews in Plant Sciences · doi:10.1080/07352689.2012.715984 · Cited by 152
Bioinformatics opportunities for identification and study of medicinal plants
Sharma, V., & Sarkar, I. N. (2013) · Briefings in Bioinformatics · doi:10.1093/bib/bbs021 · Cited by 121
Metadata
- Authors
- Lahaye, R., van der Bank, M., Bogarin, D., Warner, J., Pupulin, F., Gigot, G., Maurin, O., Duthoit, S., Barraclough, T. G., & Savolainen, V.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2008-02-26
- Volume
- 105
- Issue
- 8
- Pages
- 2923-2928
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W1996715232
- Cited by
- 911
- References
- 2
- FWCI
- 58.76
- Type
- journal article
- Language
- en
- Open access
- green
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
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.