The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Estimating Maximum Likelihood Phylogenies with PhyML
Abstract
Our understanding of the origins, the functions and/or the structures of biological sequences strongly depends on our ability to decipher the mechanisms of molecular evolution. These complex processes can be described through the comparison of homologous sequences in a phylogenetic framework. Moreover, phylogenetic inference provides sound statistical tools to exhibit the main features of molecular evolution from the analysis of actual sequences. This chapter focuses on phylogenetic tree estimation under the maximum likelihood (ML) principle. Phylogenies inferred under this probabilistic criterion are usually reliable and important biological hypotheses can be tested through the comparison of different models. Estimating ML phylogenies is computationally demanding, and careful examination of the results is warranted. This chapter focuses on PhyML, a software that implements recent ML phylogenetic methods and algorithms. We illustrate the strengths and pitfalls of this program through the analysis of a real data set. PhyML v3.0 is available from (http://atgc_montpellier.fr/phyml/).
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Cites
Kimura, M. (1980) · Journal of Molecular Evolution · doi:10.1007/bf01731581 · Cited by 29,778
Evolutionary trees from DNA sequences: A maximum likelihood approach.
Felsenstein, J. (1981) · Journal of Molecular Evolution · doi:10.1007/bf01734359 · Cited by 14,571
Evolution of Protein Molecules
JUKES, T. H., & CANTOR, C. R. (1969) · Mammalian Protein Metabolism · doi:10.1016/b978-1-4832-3211-9.50009-7 · Cited by 11,032
Dating of the human–ape splitting by a molecular clock of mitochondrial DNA.
Hasegawa, M., Kishino, H., & Yano, T.-A. (1985) · Journal of Molecular Evolution · doi:10.1007/bf02101694 · Cited by 8,687
Multiple Comparisons of Log-Likelihoods with Applications to Phylogenetic Inference
Shimodaira, H., & Hasegawa, M. (1999) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a026201 · Cited by 4,237
ProtTest: selection of best-fit models of protein evolution
Abascal, F., Zardoya, R., & Posada, D. (2005) · Bioinformatics · doi:10.1093/bioinformatics/bti263 · Cited by 3,063
Yang, Z. (1994) · Journal of Molecular Evolution · doi:10.1007/bf00160154 · Cited by 2,960
Whelan, S., & Goldman, N. (2001) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a003851 · Cited by 2,849
Cited by
FastTree 2 – Approximately Maximum-Likelihood Trees for Large Alignments
Price, M. N., Dehal, P. S., & Arkin, A. P. (2010) · PLoS ONE · doi:10.1371/journal.pone.0009490 · Cited by 14,894
The Brassica oleracea genome reveals the asymmetrical evolution of polyploid genomes
Liu, S., Liu, Y., Yang, X., Tong, C., Edwards, D., Parkin, I. A. P., Zhao, M., Ma, J., Yu, J., Huang, S., et al. (2014) · Nature Communications · doi:10.1038/ncomms4930 · Cited by 1,161
Clinical Metagenomic Sequencing for Diagnosis of Meningitis and Encephalitis
Wilson, M. R., Sample, H. A., Zorn, K. C., Arevalo, S., Yu, G., Neuhaus, J., Federman, S., Stryke, D., Briggs, B., Langelier, C., et al. (2019) · New England Journal of Medicine · doi:10.1056/nejmoa1803396 · Cited by 1,067
Co-circulation of three camel coronavirus species and recombination of MERS-CoVs in Saudi Arabia
Sabir, J. S. M., Lam, T. T.-Y., Ahmed, M. M. M., Li, L., Shen, Y., E. M. Abo-Aba, S., Qureshi, M. I., Abu-Zeid, M., Zhang, Y., Khiyami, M. A., et al. (2016) · Science · doi:10.1126/science.aac8608 · Cited by 441
Genomic signatures of evolutionary transitions from solitary to group living
Kapheim, K. M., Pan, H., Li, C., Salzberg, S. L., Puiu, D., Magoc, T., Robertson, H. M., Hudson, M. E., Venkat, A., Fischman, B. J., et al. (2015) · Science · doi:10.1126/science.aaa4788 · Cited by 409
Metadata
- Authors
- Guindon, S., Delsuc, F., Dufayard, J.-F., & Gascuel, O.
- Venue
- Methods in Molecular Biology
- Publisher
- Humana Press
- Published
- 2009
- Volume
- 537
- Pages
- 113-137
- ISSN
- 1064-3745 (ISSN-L)
- 1940-6029
- OpenAlex
- W113427216
- Cited by
- 820
- References
- 8
- FWCI
- 48.82
- Type
- book chapter
- Language
- en
- Open access
- closed
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