The DOI matches its Crossref record; 40 of the 41 references it cites were found in a registry or an index.
New Algorithms and Methods to Estimate Maximum-Likelihood Phylogenies: Assessing the Performance of PhyML 3.0
Open accessAbstract
PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/.
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“On the other hand, FastTree was found to be much faster than RAxML and PhyML but reported lower likelihood scores for data sets with both small and large numbers of sequences (Guindon et al. 2010; Price et al. 2010; Liu et al. 2011).”
From Evaluating fast maximum likelihood-based phylogenetic programs using empirical phylogenomic data sets (2018) · cites this paper as Guindon et al. 2010
In the citing paper
“In these studies, RAxML and PhyML showed largely similar performance in identifying trees of higher likelihood scores (Guindon et al. 2010; Money and Whelan 2012), whereas IQ-TREE exhibited improved efficiency compared with both RAxML and PhyML (Nguyen et al. 2015; Chernomor et al. 2016).”
From Evaluating fast maximum likelihood-based phylogenetic programs using empirical phylogenomic data sets (2018) · cites this paper as Guindon et al. 2010
In the citing paper
“However, in contrast to previous observations (Guindon et al. 2010), we found that RAxML consistently outperformed PhyML in all data sets.”
From Evaluating fast maximum likelihood-based phylogenetic programs using empirical phylogenomic data sets (2018) · cites this paper as Guindon et al. 2010
In the citing paper
“So far, these four programs have only been evaluated using simulated data (Guindon et al. 2010; Price et al. 2010; Liu et al. 2011), and empirical data sets with wide ranges of taxon numbers (e.g., up to 237,882 taxa in Price et al. [2010]) but relatively small numbers of genes (from ∼10 [Price et al. 2010; Liu et al. 2011; Chernomor et al. 2016] to ∼200 [Guindon et al. 2010; Money and Whelan 2012”
From Evaluating fast maximum likelihood-based phylogenetic programs using empirical phylogenomic data sets (2018) · cites this paper as Guindon et al. 2010
In the citing paper
“This difference might be due to the small number of alignments examined in the previous study (Guindon et al. 2010) and the numerous updates of both programs since then.”
From Evaluating fast maximum likelihood-based phylogenetic programs using empirical phylogenomic data sets (2018) · cites this paper as Guindon et al. 2010
In the citing paper
“Overall, our results at the level of single-gene tree inference are consistent with previous, smaller-scale studies on the better efficiency of IQ-TREE relative to RAxML and PhyML (all using one search per alignment) (Nguyen et al. 2015), and the inferior performance of FastTree in likelihood score maximization when compared with other programs (Guindon et al. 2010; Liu et al. 2011).”
From Evaluating fast maximum likelihood-based phylogenetic programs using empirical phylogenomic data sets (2018) · cites this paper as Guindon et al. 2010
In the citing paper
“Such differential behavior may be attributed to the distinct algorithmic designs and/or software implementations of the programs on protein and DNA data (Guindon et al. 2010).”
From Evaluating fast maximum likelihood-based phylogenetic programs using empirical phylogenomic data sets (2018) · cites this paper as Guindon et al. 2010
In the citing paper
“in agreement with previous studies (Guindon et al. 2010; Nguyen et al. 2015), we found that some programs displayed different time efficiency on protein and DNA data sets”
From Evaluating fast maximum likelihood-based phylogenetic programs using empirical phylogenomic data sets (2018) · cites this paper as Guindon et al. 2010
In the citing paper
“A potential explanation could be that IQ-TREE uses NNI as its topological rearrangement mechanism (Nguyen et al. 2015), whereas RAxML and PhyML are both based on SPR (Stamatakis 2006; Guindon et al. 2010).”
From Evaluating fast maximum likelihood-based phylogenetic programs using empirical phylogenomic data sets (2018) · cites this paper as Guindon et al. 2010
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
1 retracted
RETRACTED ARTICLE: TREEFINDER: a powerful graphical analysis environment for molecular phylogenetics
Jobb, G., von Haeseler, A., & Strimmer, K. (2004) · BMC Evolutionary Biology · doi:10.1186/1471-2148-4-18 · Cited by 1,109
RetractedCONFIDENCE LIMITS ON PHYLOGENIES: AN APPROACH USING THE BOOTSTRAP
Felsenstein, J. (1985) · Evolution · doi:10.1111/j.1558-5646.1985.tb00420.x · Cited by 44,735
MrBayes 3: Bayesian phylogenetic inference under mixed models
Ronquist, F., & Huelsenbeck, J. P. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btg180 · Cited by 29,194
A Simple, Fast, and Accurate Algorithm to Estimate Large Phylogenies by Maximum Likelihood
Guindon, S., & Gascuel, O. (2003) · Systematic Biology · doi:10.1080/10635150390235520 · Cited by 16,923
Self-citationRAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models
Stamatakis, A. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl446 · Cited by 15,582
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
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
A Rapid Bootstrap Algorithm for the RAxML Web Servers
Stamatakis, A., Hoover, P., & Rougemont, J. (2008) · Systematic Biology · doi:10.1080/10635150802429642 · Cited by 7,028
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
Kishino, H., & Hasegawa, M. (1989) · Journal of Molecular Evolution · doi:10.1007/bf02100115 · Cited by 3,310
Flagged first, then by citations
1 of the 41 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- Sanderson, 1994, TreeBASE: a prototype database of phylogenetic analyses and an interactive tool for browsing the phylogeny of life, Am. J. Bot, 81, 183
Cited by
Sorted by citations
Items 1,001–1,061 of 1,061
Common ancestry of iron oxide- and iron-sulfide-based biomineralization in magnetotactic bacteria
Abreu, F. D. Á., Cantão, M. E., Nicolás, M., Barcellos, F. G., Morillo, V., de Almeida, L. G. P., do Nascimento, F. F., Lefèvre, C. T., Bazylinski, D. A., de Vasconcelos, A. T. R., et al. (2011) · The ISME Journal · doi:10.1038/ismej.2011.35 · Cited by 107
Aureochrome 1a Is Involved in the Photoacclimation of the Diatom Phaeodactylum tricornutum
Costa, B. S., Sachse, M., Jungandreas, A., Bártulos, C. R., Gruber, A., Jakob, T., Kroth, P. G., & Wilhelm, C. (2013) · PLoS ONE · doi:10.1371/journal.pone.0074451 · Cited by 107
Borneman, A. R., McCarthy, J. M., Chambers, P. J., & Bartowsky, E. J. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-373 · Cited by 112
Turner, A. G., Ong, C.-L. Y., Gillen, C. M., Davies, M. R., West, N. P., McEwan, A. G., & Walker, M. J. (2015) · mBio · doi:10.1128/mbio.00278-15 · Cited by 93
Stress-Tolerant Yeasts: Opportunistic Pathogenicity Versus Biocontrol Potential
Zajc, J., Gostinčar, C., Černoša, A., & Gunde-Cimerman, N. (2019) · Genes · doi:10.3390/genes10010042 · Cited by 87
Ehrmann, I., Dalgliesh, C., Liu, Y., Danilenko, M., Crosier, M., Overman, L., Arthur, H. M., Lindsay, S., Clowry, G. J., Venables, J. P., et al. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003474 · Cited by 82
Gene duplicates cause hybrid lethality between sympatric species of Mimulus
Zuellig, M. P., & Sweigart, A. L. (2018) · PLOS Genetics · doi:10.1371/journal.pgen.1007130 · Cited by 82
The Comb Jelly Opsins and the Origins of Animal Phototransduction
Feuda, R., Rota-Stabelli, O., Oakley, T. H., & Pisani, D. (2014) · Genome Biology and Evolution · doi:10.1093/gbe/evu154 · Cited by 70
Allopatric speciation within a cryptic species complex of Australasian octopuses
Amor, M. D., Norman, M. D., Cameron, H. E., & Strugnell, J. M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0098982 · Cited by 79
Convergent Evolution of Sodium Ion Selectivity in Metazoan Neuronal Signaling
Gur Barzilai, M., Reitzel, A. M., Kraus, J. E. M., Gordon, D., Technau, U., Gurevitz, M., & Moran, Y. (2012) · Cell Reports · doi:10.1016/j.celrep.2012.06.016 · Cited by 76
Lawley, J. W., Gamero-Mora, E., Maronna, M. M., Chiaverano, L. M., Stampar, S. N., Hopcroft, R. R., Collins, A. G., & Morandini, A. C. (2021) · PeerJ · doi:10.7717/peerj.11954 · Cited by 71
“, 2017) for model selection and measuring bootstrap resampling frequencies and SH-aLRT (Guindon et al., 2010) from 1,000 pseudoreplicates.”
BackgroundMethodInfluentialA Unique Clade of SARS-CoV-2 Viruses is Associated with Lower Viral Loads in Patient Upper Airways
Lorenzo-Redondo, R., Nam, H. H., Roberts, S. C., Simons, L. M., Jennings, L. J., Qi, C., Achenbach, C. J., Hauser, A. R., Ison, M. G., Hultquist, J. F., et al. (2020) · doi:10.1101/2020.05.19.20107144 · Cited by 111
“11 (21), assessing the tree topology with the Shimodaira–Hasegawa approximate likelihood ratio test (SH-aLRT) (22) with 1000 replicates.”
A YidC-like protein in the archaeal plasma membrane.
Borowska, M. T., Dominik, P. K., Anghel, S. A., Kossiakoff, A. A., & Keenan, R. J. (2015) · Structure · doi:10.1016/j.str.2015.06.025 · Cited by 71
New genomic data and analyses challenge the traditional vision of animal epithelium evolution
Belahbib, H., Renard, E., Santini, S., Jourda, C., Claverie, J.-M., Borchiellini, C., & Le Bivic, A. (2018) · BMC Genomics · doi:10.1186/s12864-018-4715-9 · Cited by 71
Assmann, M., Kuhn, A., Dürrnagel, S., Holstein, T. W., & Gründer, S. (2014) · BMC Biology · doi:10.1186/s12915-014-0084-2 · Cited by 70
RGM Regulates BMP-Mediated Secondary Axis Formation in the Sea Anemone Nematostella vectensis
Leclère, L., & Rentzsch, F. (2014) · Cell Reports · doi:10.1016/j.celrep.2014.11.009 · Cited by 67
Diversity and evolution of myxozoan minicollagens and nematogalectins
Shpirer, E., Chang, E. S., Diamant, A., Rubinstein, N., Cartwright, P., & Huchon, D. (2014) · BMC Evolutionary Biology · doi:10.1186/s12862-014-0205-0 · Cited by 63
Voigt, O., Adamski, M., Sluzek, K., & Adamska, M. (2014) · BMC Evolutionary Biology · doi:10.1186/s12862-014-0230-z · Cited by 63
Duchêne, D. A., Tong, K. J., Foster, C. S. P., Duchêne, S., Lanfear, R., & Ho, S. Y. W. (2020) · Molecular Biology and Evolution · doi:10.1093/molbev/msz291 · Cited by 53
Scalable empirical mixture models that account for across-site compositional heterogeneity
Schrempf, D., Lartillot, N., & Szöllősi, G. (2019) · doi:10.1101/794263 · Cited by 61
Yamada, N., Sym, S. D., & Horiguchi, T. (2017) · Molecular Biology and Evolution · doi:10.1093/molbev/msx054 · Cited by 59
Himsworth, C. G., Miller, R. R., Montoya, V., Hoang, L., Romney, M. G., Al-Rawahi, G. N., Kerr, T., Jardine, C. M., Patrick, D. M., Tang, P., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0087983 · Cited by 60
“To determine phylogenetic relationships among isolates, maximum-likelihood trees were generated from the entire genome sequence using PhyML [23] with the HKY85 substitution model, MRSA Carriage in Wild Rats”
MethodPhylogenetic Analysis of the Kinesin Superfamily from Physcomitrella
Shen, Z., Collatos, A. R., Bibeau, J. P., Furt, F., & Vidali, L. (2012) · Frontiers in Plant Science · doi:10.3389/fpls.2012.00230 · Cited by 60
Petzold, A., & Hassanin, A. (2020) · PLOS ONE · doi:10.1371/journal.pone.0217956 · Cited by 60
A family of diatom-like silicon transporters in the siliceous loricate choanoflagellates
Marron, A. O., Alston, M. J., Heavens, D., Akam, M., Caccamo, M., Holland, P. W. H., & Walker, G. (2013) · Proceedings of the Royal Society B: Biological Sciences · doi:10.1098/rspb.2012.2543 · Cited by 54
Ancient DNA Reveals Evidence of Abundant Aurochs (Bos Primigenius) in Neolithic Northeast China
Cai, D., Zhang, N., Zhu, S., Chen, Q., Wang, L., Zhao, X., Ma, X., Royle, T. C. A., Zhou, H., & Yang, D. Y. (2018) · Journal of Archaeological Science · doi:10.1016/j.jas.2018.08.003 · Cited by 55
Staphylococcus lugdunensis IsdG Liberates Iron from Host Heme
Haley, K. P., Janson, E. M., Heilbronner, S., Foster, T. J., & Skaar, E. P. (2011) · Journal of Bacteriology · doi:10.1128/jb.00436-11 · Cited by 53
Kulke, D., von Samson-Himmelstjerna, G., Miltsch, S. M., Wolstenholme, A. J., Jex, A. R., Gasser, R. B., Ballesteros, C., Geary, T. G., Keiser, J., Townson, S., et al. (2014) · PLoS Neglected Tropical Diseases · doi:10.1371/journal.pntd.0003401 · Cited by 52
Habib, N., Wapinski, I., Margalit, H., Regev, A., & Friedman, N. (2012) · Molecular Systems Biology · doi:10.1038/msb.2012.50 · Cited by 50
Pei, Z., Liu, Y., Chen, Y., Pan, T., Sun, X., Wang, H., Ross, R. P., Lu, W., & Chen, W. (2024) · Gut Microbes · doi:10.1080/19490976.2024.2309684 · Cited by 48
“The construction of the phylogenetic tree was executed using phyML v. 3.1, 55 employing the neighbor-joining method and based on the entire prophage genomes.”
MethodInfluentialRed fox viromes in urban and rural landscapes
Campbell, S. J., Ashley, W., Gil-Fernandez, M., Newsome, T. M., Di Giallonardo, F., Ortiz-Baez, A. S., Mahar, J. E., Towerton, A. L., Gillings, M., Holmes, E. C., et al. (2020) · Virus Evolution · doi:10.1093/ve/veaa065 · Cited by 47
Godfroid, M., Dagan, T., & Kupczok, A. (2018) · Genome Biology and Evolution · doi:10.1093/gbe/evy143 · Cited by 37
Xu, T., Qin, S., Hu, Y., Song, Z., Ying, J., Li, P., Dong, W., Zhao, F., Yang, H., & Bao, Q. (2016) · DNA Research · doi:10.1093/dnares/dsw023 · Cited by 37
“0 with 1,000 bootstrap replications.(19) The protein-coding gene derived from four Arthrospira genomes was predicted using the same criteria as earlier described.”
MethodThe evolution of the dystroglycan complex, a major mediator of muscle integrity
Adams, J. C., & Brancaccio, A. (2015) · Biology Open · doi:10.1242/bio.012468 · Cited by 35
Amor, M. D., Laptikhovsky, V., Norman, M. D., & Strugnell, J. M. (2017) · Journal of the Marine Biological Association of the United Kingdom · doi:10.1017/s0025315415000958 · Cited by 37
Putative Monofunctional Type I Polyketide Synthase Units: A Dinoflagellate-Specific Feature?
Eichholz, K., Beszteri, B., & John, U. (2012) · PLoS ONE · doi:10.1371/journal.pone.0048624 · Cited by 37
From primordial clocks to circadian oscillators
Pitsawong, W., Pádua, R. A. P., Grant, T., Hoemberger, M., Otten, R., Bradshaw, N., Grigorieff, N., & Kern, D. (2023) · Nature · doi:10.1038/s41586-023-05836-9 · Cited by 37
Liang, L., Yi, Y., Lv, Y., Qian, J., Lei, X., & Zhang, G. (2018) · Molecules · doi:10.3390/molecules23051157 · Cited by 38
Oxygen metabolism in descendants of the archaeal-eukaryotic ancestor
Appler, K. E., Lingford, J. P., Gong, X., Panagiotou, K., Leão, P., Langwig, M. V., Greening, C., Ettema, T. J. G., De Anda, V., & Baker, B. J. (2026) · Nature · doi:10.1038/s41586-026-10128-z · Cited by 36
Oxygen metabolism in descendants of the archaeal-eukaryotic ancestor
Appler, K. E., Lingford, J. P., Gong, X., Panagiotou, K., Leão, P., Langwig, M., Greening, C., Ettema, T. J. G., De Anda, V., & Baker, B. J. (2024) · doi:10.1101/2024.07.04.601786 · Cited by 36
The Genomic Natural History of the Aurochs
Rossi, C., Sinding, M.-H. S., Mullin, V. E., Scheu, A., Erven, J. A. M., Verdugo, M. P., Daly, K. G., Ciucani, M. M., Mattiangeli, V., Teasdale, M. D., et al. (2024) · Nature · doi:10.1038/s41586-024-08112-6 · Cited by 32
Highly replicated evolution of parapatric ecotypes
James, M. E., Arenas-Castro, H., Groh, J. S., Allen, S. L., Engelstädter, J., & Ortiz-Barrientos, D. (2021) · Molecular Biology and Evolution · doi:10.1093/molbev/msab207 · Cited by 30
The molecular signal for the adaptation to cold temperature during early life on Earth
Groussin, M., Boussau, B., Charles, S., Blanquart, S., & Gouy, M. (2013) · Biology Letters · doi:10.1098/rsbl.2013.0608 · Cited by 29
Hultqvist, G., Ocampo Daza, D., Larhammar, D., & Kilimann, M. W. (2012) · PLoS ONE · doi:10.1371/journal.pone.0041850 · Cited by 27
Kroll, K., Shekhova, E., Mattern, D. J., Thywissen, A., Jacobsen, I. D., Strassburger, M., Heinekamp, T., Shelest, E., Brakhage, A. A., & Kniemeyer, O. (2016) · Molecular Microbiology · doi:10.1111/mmi.13377 · Cited by 22
The unique evolution of the programmed cell death 4 protein in plants
Cheng, S., Liu, R., & Gallie, D. R. (2013) · BMC Evolutionary Biology · doi:10.1186/1471-2148-13-199 · Cited by 22
Dudas, G., Hong, S. L., Potter, B., Calvignac-Spencer, S., Niatou-Singa, F. S., Tombolomako, T. B., Fuh-Neba, T., Vickos, U., Ulrich, M., Leendertz, F. H., et al. (2021) · doi:10.1101/2021.05.04.21256637 · Cited by 76
“New582 algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of583 PhyML 3.0.”
MethodInfluentialEarly Pleistocene enamel proteome sequences from Dmanisi resolve Stephanorhinus phylogeny
Cappellini, E., Welker, F., Pandolfi, L., Madrigal, J. R., Fotakis, A. K., Lyon, D., Moreno Mayar, V. J., Bukhsianidze, M., Jersie-Christensen, R. R., Mackie, M., et al. (2018) · doi:10.1101/407692 · Cited by 20
Highly iterated palindromic sequences (HIPs) and their relationship to DNA methyltransferases
Elhai, J. (2015) · Life · doi:10.3390/life5010921 · Cited by 20
Deep learning and CRISPR-Cas13d ortholog discovery for optimized RNA targeting
Wei, J., Lotfy, P., Faizi, K., Baungaard, S., Gibson, E., Wang, E., Slabodkin, H., Kinnaman, E., Chandrasekaran, S., Kitano, H., et al. (2021) · doi:10.1101/2021.09.14.460134 · Cited by 67
MAP9/MAPH-9 supports axonemal microtubule doublets and modulates motor movement
Tran, M. V., Khuntsariya, D., Fetter, R. D., Ferguson, J. W., Wang, J. T., Long, A. F., Cote, L. E., Wellard, S. R., Vázquez-Martínez, N., Sallee, M. D., et al. (2024) · Developmental Cell · doi:10.1016/j.devcel.2023.12.001 · Cited by 18
Molecular Basis for the Evolution of Species-Specific Hemoglobin Capture by Staphylococcus aureus
Choby, J. E., Buechi, H. B., Farrand, A. J., Skaar, E. P., & Barber, M. F. (2018) · mBio · doi:10.1128/mbio.01524-18 · Cited by 15
Function and evolution of two forms of SecDF homologs in Streptomyces coelicolor.
Zhou, Z., Li, Y., Sun, N., Sun, Z., Lv, L., Wang, Y., Shen, L., & Li, Y.-Q. (2014) · PLoS ONE · doi:10.1371/journal.pone.0105237 · Cited by 13
Genomic Characteristion of Opportunistic Pathogen Kluyvera Reveals a Novel CTX-M Subgroup
Yu, K., Huang, Z., Lan, R., Morris, J. G., Xiao, Y., Fu, S., Gao, H., Bai, X., Li, K., & Wang, D. (2023) · Microorganisms · doi:10.3390/microorganisms11122836 · Cited by 12
Nahas, J. V., Iosue, C. L., Shaik, N. F., Selhorst, K., He, B. Z., & Wykoff, D. D. (2018) · G3 Genes Genomes Genetics · doi:10.1534/g3.118.200303 · Cited by 8
Todesco, E., Day, N., Amiel, C., Elaerts, S., Schneider, V., Roudière, L., Hué, S., Liotier, J.-Y., Bottero, J., L'Yavanc, T., et al. (2019) · International Journal of Antimicrobial Agents · doi:10.1016/j.ijantimicag.2019.02.002 · Cited by 7
Evolution of g-type lysozymes in metazoa: insights into immunity and digestive adaptations
Mukherjee, K., & Moroz, L. L. (2024) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2024.1487920 · Cited by 7
Bian, C., 深圳大学生命与海洋科学学院水产基因组学实验室, 广. 深. 5., Laboratory of Aquatic Genomics, C. O. L. S. A. O., Li, R.-H., Ruan, Z.-Q., Chen, W.-T., Huang, Y., Liu, L.-Y., Zhou, H.-L., Chong, C.-M., et al. (2024) · Zoological Research · doi:10.24272/j.issn.2095-8137.2023.396 · Cited by 4
Exploring fern pathosystems and immune receptors to bridge gaps in plant immunity
Castel, B., Baker, M., Keller, J., Martinez, Y., Bonhomme, M., Delaux, P.-M., & Jacquet, C. (2025) · BMC Biology · doi:10.1186/s12915-025-02413-6 · Cited by 4
Adhikari, A., Feng, K. H., Shrestha, A., Rodriguez, C. E., Nolan, E. C., Pye, G. W., Gauger, P. C., Denagamage, T., Holmes, E. C., & Allison, A. B. (2026) · PLOS Pathogens · doi:10.1371/journal.ppat.1013861 · Cited by 1
“Phylogenetic trees of each data set were then inferred using the maximum likelihood (ML) method available in the PhyML package [91].”
Abedin, I., Putra, A., Kang, H.-E., Singh, A., Singh, S., Jung, W.-K., Kim, H.-W., & Kundu, S. (2025) · doi:10.21203/rs.3.rs-7140563/v1 · Cited by 1
Metadata
- Authors
- Guindon, S., Dufayard, J.-F., Lefort, V., Anisimova, M., Hordijk, W., & Gascuel, O.
- Affiliations
- Centre National de la Recherche Scientifique (FR)
- SIB Swiss Institute of Bioinformatics (CH)
- Corresponding author
- Gascuel, Olivier
- ORCID
- Venue
- Systematic Biology
- Publisher
- Oxford University Press (OUP)
- Published
- 2010-03-29
- Volume
- 59
- Issue
- 3
- Pages
- 307-321
- ISSN
- 1063-5157 (ISSN-L)
- 1076-836X
- OpenAlex
- W2111211467
- Cited by
- 18,376
- References
- 41
- Citations by year
- 2026: 1054 · 2025: 1310 · 2024: 1284 · 2023: 1304 · 2022: 1541 · 2021: 1787 · 2020: 1614 · 2019: 1428 · 2018: 1301 · 2017: 1148 · 2016: 1113 · 2015: 1006 · 2014: 1002 · 2013: 748 · 2012: 507
- FWCI
- 190.74
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Systematic Biology (publishedVersion)
- PubMed (publishedVersion)
- Zurich Open Repository and Archive (University of Zurich) (acceptedVersion, other-oa)
- HAL (submittedVersion, other-oa)
- reroDoc Digital Library (submittedVersion)
- Repository for Publications and Research Data (ETH Zurich) (submittedVersion, other-oa)
- ResearchSpace (University of Auckland) (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion, other-oa)
- ETH Zürich Research Collection
- Zurich Open Repository and Archive (University of Zurich)
- Funders
- Agence Nationale de la Recherche
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Physical Sciences › Earth and Planetary Sciences › Paleontology › Evolution and Paleontology Studies
- Keywords
- PhyML, maximum likelihood phylogenetic inference, nonparametric bootstrap
- MeSH terms
- Algorithms, Classification, Phylogeny, Software, Likelihood Functions
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
