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Bias and artifacts in multitemplate polymerase chain reactions (PCR)
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Citations
Cited by
UniFrac: a New Phylogenetic Method for Comparing Microbial Communities
Lozupone, C., & Knight, R. (2005) · Applied and Environmental Microbiology · doi:10.1128/aem.71.12.8228-8235.2005 · Cited by 8,227
Detection of ultra-rare mutations by next-generation sequencing
Schmitt, M. W., Kennedy, S. R., Salk, J. J., Fox, E. J., Hiatt, J. B., & Loeb, L. A. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1208715109 · Cited by 1,047
Srinivasan, S., Hoffman, N. G., Morgan, M. T., Matsen, F. A., Fiedler, T. L., Hall, R. W., Ross, F. J., McCoy, C. O., Bumgarner, R., Marrazzo, J. M., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0037818 · Cited by 673
The Madness of Microbiome: Attempting To Find Consensus “Best Practice” for 16S Microbiome Studies
Pollock, J., Glendinning, L., Wisedchanwet, T., & Watson, M. (2018) · Applied and Environmental Microbiology · doi:10.1128/aem.02627-17 · Cited by 575
The truth about metagenomics: quantifying and counteracting bias in 16S rRNA studies
Vaginal Microbiome Consortium (additional members), Brooks, J. P., Edwards, D. J., Harwich, M. D., Rivera, M. C., Fettweis, J. M., Serrano, M. G., Reris, R. A., Sheth, N. U., Huang, B., et al. (2015) · BMC Microbiology · doi:10.1186/s12866-015-0351-6 · Cited by 528
Dabney, J., & Meyer, M. (2012) · BioTechniques · doi:10.2144/000113809 · Cited by 316
Animal-to-animal variation in fecal microbial diversity among beef cattle
Durso, L. M., Harhay, G. P., Smith, T. P. L., Bono, J. L., DeSantis, T. Z., Harhay, D. M., Andersen, G. L., Keen, J. E., Laegreid, W. W., & Clawson, M. L. (2010) · Applied and Environmental Microbiology · doi:10.1128/aem.00207-10 · Cited by 168
Evolution favors protein mutational robustness in sufficiently large populations
Bloom, J. D., Lu, Z., Chen, D., Raval, A., Venturelli, O. S., & Arnold, F. H. (2007) · BMC Biology · doi:10.1186/1741-7007-5-29 · Cited by 119
Sources of Error in Mammalian Genetic Screens
Sack, L. M., Davoli, T., Xu, Q., Li, M. Z., & Elledge, S. J. (2016) · G3 Genes|Genomes|Genetics · doi:10.1534/g3.116.030973 · Cited by 76
High-throughput sequencing SELEX for the determination of DNA-binding protein specificities in vitro
Pantier, R., Chhatbar, K., Alston, G., Lee, H. Y., & Bird, A. (2022) · STAR Protocols · doi:10.1016/j.xpro.2022.101490 · Cited by 28
Protocol for the functional evaluation of genetic variants using saturation genome editing
Obolenski, S., Olvera-León, R., Sun, D., Adams, D. J., & Waters, A. J. (2025) · STAR Protocols · doi:10.1016/j.xpro.2025.103710 · Cited by 3
Metadata
- Authors
- Kanagawa, T.
- Venue
- Journal of Bioscience and Bioengineering
- Publisher
- Elsevier BV
- Published
- 2003-01
- Volume
- 96
- Issue
- 4
- Pages
- 317-323
- ISSN
- 1347-4421 (ISSN-L)
- 1389-1723
- OpenAlex
- W2088170018
- Cited by
- 566
- References
- 0
- FWCI
- 3.75
- Type
- journal article
- Language
- en
- Open access
- closed
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.
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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.