The DOI matches its Crossref record; 85 of the 85 references it cites were found in a registry or an index.
Measurably evolving pathogens in the genomic era
Open accessAbstract
Current sequencing technologies have created unprecedented opportunities for studying microbial populations. For pathogens with comparatively low per-site mutation rates, such as DNA viruses and bacteria, whole-genome sequencing can reveal the accumulation of novel genetic variation between population samples taken at different times. The concept of “measurably evolving populations” and related analytical approaches have provided powerful insights for fast-evolving RNA viruses, but their application to other pathogens is still in its infancy. Here we argue that previous distinctions between slow- and fast-evolving pathogens become blurred once evolution is assessed at a genome-wide scale and we highlight important analytical challenges to be overcome in order to infer pathogen population dynamics from genomic data.
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Cites
BEAST: Bayesian evolutionary analysis by sampling trees
Drummond, A. J., & Rambaut, A. (2007) · BMC Evolutionary Biology · doi:10.1186/1471-2148-7-214 · Cited by 12,919
Relaxed Phylogenetics and Dating with Confidence
Drummond, A. J., Ho, S. Y. W., Phillips, M. J., & Rambaut, A. (2006) · PLoS Biology · doi:10.1371/journal.pbio.0040088 · Cited by 6,463
progressiveMauve: Multiple Genome Alignment with Gene Gain, Loss and Rearrangement
Darling, A. E., Mau, B., & Perna, N. T. (2010) · PLoS ONE · doi:10.1371/journal.pone.0011147 · Cited by 3,848
Bayesian Coalescent Inference of Past Population Dynamics from Molecular Sequences
Drummond, A. J. (2005) · Molecular Biology and Evolution · doi:10.1093/molbev/msi103 · Cited by 3,143
Rates of evolutionary change in viruses: patterns and determinants
Duffy, S., Shackelton, L. A., & Holmes, E. C. (2008) · Nature Reviews Genetics · doi:10.1038/nrg2323 · Cited by 1,551
Genotype and SNP calling from next-generation sequencing data
Nielsen, R., Paul, J. S., Albrechtsen, A., & Song, Y. S. (2011) · Nature Reviews Genetics · doi:10.1038/nrg2986 · Cited by 1,396
Unifying the Epidemiological and Evolutionary Dynamics of Pathogens
Grenfell, B. T., Pybus, O. G., Gog, J. R., Wood, J. L. N., Daly, J. M., Mumford, J. A., & Holmes, E. C. (2004) · Science · doi:10.1126/science.1090727 · Cited by 1,385
Self-citationEvolution of MRSA During Hospital Transmission and Intercontinental Spread
Harris, S. R., Feil, E. J., Holden, M. T. G., Quail, M. A., Nickerson, E. K., Chantratita, N., Gardete, S., Tavares, A., Day, N., Lindsay, J. A., et al. (2010) · Science · doi:10.1126/science.1182395 · Cited by 1,091
Out-of-Africa migration and Neolithic coexpansion of Mycobacterium tuberculosis with modern humans
Comas, I., Coscolla, M., Luo, T., Borrell, S., Holt, K. E., Kato-Maeda, M., Parkhill, J., Malla, B., Berg, S., Thwaites, G., et al. (2013) · Nature Genetics · doi:10.1038/ng.2744 · Cited by 1,025
Walker, T. M., Ip, C. L., Harrell, R. H., Evans, J. T., Kapatai, G., Dedicoat, M. J., Eyre, D. W., Wilson, D. J., Hawkey, P. M., Crook, D. W., et al. (2013) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(12)70277-3 · Cited by 918
Cited by
Exploring the temporal structure of heterochronous sequences using TempEst (formerly Path-O-Gen)
Rambaut, A., Lam, T. T., Max Carvalho, L., & Pybus, O. G. (2016) · Virus Evolution · doi:10.1093/ve/vew007 · Cited by 2,063
Self-citationTracking virus outbreaks in the twenty-first century
Grubaugh, N. D., Ladner, J. T., Lemey, P., Pybus, O. G., Rambaut, A., Holmes, E. C., & Andersen, K. G. (2018) · Nature Microbiology · doi:10.1038/s41564-018-0296-2 · Cited by 485
Self-citationWhole genome sequencing of Mycobacterium tuberculosis: current standards and open issues
Meehan, C. J., Goig, G. A., Kohl, T. A., Verboven, L., Dippenaar, A., Ezewudo, M., Farhat, M. R., Guthrie, J. L., Laukens, K., Miotto, P., et al. (2019) · Nature Reviews Microbiology · doi:10.1038/s41579-019-0214-5 · Cited by 422
Temporal signal and the phylodynamic threshold of SARS-CoV-2
Duchene, S., Featherstone, L., Haritopoulou-Sinanidou, M., Rambaut, A., Lemey, P., & Baele, G. (2020) · Virus Evolution · doi:10.1093/ve/veaa061 · Cited by 384
Metadata
- Authors
- Biek, R., Pybus, O. G., Lloyd-Smith, J. O., & Didelot, X.
- Venue
- Trends in Ecology & Evolution
- Publisher
- Elsevier BV
- Published
- 2015-06
- Volume
- 30
- Issue
- 6
- Pages
- 306-313
- ISSN
- 0169-5347 (ISSN-L)
- OpenAlex
- W2001750285
- Cited by
- 258
- References
- 85
- FWCI
- 3.72
- Type
- journal article
- Language
- en
- Open access
- bronze
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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