A Rapid Bootstrap Algorithm for the RAxML Web Servers
Open accessAbstract
Despite recent advances achieved by application of high-performance computing methods and novel algorithmic techniques to maximum likelihood (ML)-based inference programs, the major computational bottleneck still consists in the computation of bootstrap support values. Conducting a probably insufficient number of 100 bootstrap (BS) analyses with current ML programs on large datasets-either with respect to the number of taxa or base pairs-can easily require a month of run time. Therefore, we have developed, implemented, and thoroughly tested rapid bootstrap heuristics in RAxML (Randomized Axelerated Maximum Likelihood) that are more than an order of magnitude faster than current algorithms. These new heuristics can contribute to resolving the computational bottleneck and improve current methodology in phylogenetic analyses. Computational experiments to assess the performance and relative accuracy of these heuristics were conducted on 22 diverse DNA and AA (amino acid), single gene as well as multigene, real-world alignments containing 125 up to 7764 sequences. The standard BS (SBS) and rapid BS (RBS) values drawn on the best-scoring ML tree are highly correlated and show almost identical average support values. The weighted RF (Robinson-Foulds) distance between SBS- and RBS-based consensus trees was smaller than 6% in all cases (average 4%). More importantly, RBS inferences are between 8 and 20 times faster (average 14.73) than SBS analyses with RAxML and between 18 and 495 times faster than BS analyses with competing programs, such as PHYML or GARLI. Moreover, this performance improvement increases with alignment size. Finally, we have set up two freely accessible Web servers for this significantly improved version of RAxML that provide access to the 200-CPU cluster of the Vital-IT unit at the Swiss Institute of Bioinformatics and the 128-CPU cluster of the CIPRES project at the San Diego Supercomputer Center. These Web servers offer the possibility to conduct large-scale phylogenetic inferences to a large part of the community that does not have access to, or the expertise to use, high-performance computing resources.
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The support values in the phylogenetic system were generated using 100 rounds of the Rapid bootstrapping option of RAxML.
“The support values in the system are generated using 100 rounds of the “Rapid” bootstrapping option [28] of RAxML (8.2.11).”
From Genomic Characterization of Lactiplantibacillus plantarum Strains: Potential Probiotics from Ethiopian Traditional Fermented Cottage Cheese (2024) · cites this paper as [28]
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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 · see citing works
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 · see citing works
MrBayes 3: Bayesian phylogenetic inference under mixed models
Ronquist, F., & Huelsenbeck, J. P. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btg180 · Cited by 28,956 · see citing works
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 16,698 · see citing works
RAxML-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 · see citing works
Self-citationEvolutionary trees from DNA sequences: A maximum likelihood approach.
Felsenstein, J. (1981) · Journal of Molecular Evolution · doi:10.1007/bf01734359 · Cited by 14,571 · see citing works
PAUP^* : Phylogenetic Analysis Using Parsimony (and other methods) 4.0b8
Swofford, D. L. (2001) · Cited by 12,783 · see citing works
Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB
DeSantis, T. Z., Hugenholtz, P., Larsen, N., Rojas, M., Brodie, E. L., Keller, K., Huber, T., Dalevi, D., Hu, P., & Andersen, G. L. (2006) · Applied and Environmental Microbiology · doi:10.1128/aem.03006-05 · Cited by 10,891 · see citing works
PAUP * [Phylogenetic Analysis Using Parsimony (and Other Methods)]
Cummings, M. P. (2004) · Dictionary of Bioinformatics and Computational Biology · doi:10.1002/0471650129.dob0522 · Cited by 5,229 · see citing works
Zwickl, D. J. (2006) · Texas ScholarWorks (Texas Digital Library) · Cited by 3,133 · see citing works
Comparison of phylogenetic trees
Robinson, D. F., & Foulds, L. R. (1981) · Mathematical Biosciences · doi:10.1016/0025-5564(81)90043-2 · Cited by 2,990 · see citing works
Approximate likelihood-ratio test for branches: A fast, accurate, and powerful alternative
Anisimova, M., & Gascuel, O. (2006) · Systematic Biology · doi:10.1080/10635150600755453 · Cited by 2,693 · see citing works
Quartet Puzzling: A Quartet Maximum-Likelihood Method for Reconstructing Tree Topologies
Strimmer, K., & von Haeseler, A. (1996) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a025664 · Cited by 2,531 · see citing works
TREE-PUZZLE: maximum likelihood phylogenetic analysis using quartets and parallel computing
Schmidt, H. A., Strimmer, K., Vingron, M., & von Haeseler, A. (2002) · Bioinformatics · doi:10.1093/bioinformatics/18.3.502 · Cited by 2,512 · see citing works
Broad phylogenomic sampling improves resolution of the animal tree of life
Dunn, C. W., Hejnol, A., Matus, D. Q., Pang, K., Browne, W. E., Smith, S. A., Seaver, E., Rouse, G. W., Obst, M., Edgecombe, G. D., et al. (2008) · Nature · doi:10.1038/nature06614 · Cited by 1,921 · cited 1× · see citing works
“…datasets of more than 1000 sequences as used in our computational experiments are still relatively uncommon, memory requirements of ML programs are becoming increasingly important in the context of multi-gene analyses (see, for instance, McMahon and Sanderson, 2006, or Dunn et al., 2008).”
BackgroundPHYML Online--a web server for fast maximum likelihood-based phylogenetic inference
Guindon, S., Lethiec, F., Duroux, P., & Gascuel, O. (2005) · Nucleic Acids Research · doi:10.1093/nar/gki352 · Cited by 1,498 · see citing works
RAxML-III: a fast program for maximum likelihood-based inference of large phylogenetic trees
Stamatakis, A., Ludwig, T. G., & Meier, H. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bti191 · Cited by 1,429 · see citing works
Self-citationLikelihood-Based Tests of Topologies in Phylogenetics
Goldman, N., Anderson, J. P., & Rodrigo, A. G. (2000) · Systematic Biology · doi:10.1080/106351500750049752 · Cited by 1,076 · see citing works
Phylogenetic models of rate heterogeneity: A high performance computing perspective
Stamatakis, A. (2006) · Cited by 298 · see citing works
Self-citationPhylogenetic models of rate heterogeneity: a high performance computing perspective
Stamatakis, A. (2006) · IEEE International Parallel and Distributed Processing Symposium (IPDPS) · doi:10.1109/ipdps.2006.1639535 · Cited by 284 · see citing works
Self-citationAnalysis and Visualization of Tree Space
Hillis, D. M., Heath, T. A., & John, K. S. (2005) · Systematic Biology · doi:10.1080/10635150590946961 · Cited by 238 · see citing works
Hordijk, W., & Gascuel, O. (2005) · Bioinformatics · doi:10.1093/bioinformatics/bti713 · Cited by 213 · see citing works
Comparison of weighted labelled trees
Robinson, D. F., & Foulds, L. R. (1979) · Lecture notes in mathematics · doi:10.1007/bfb0102690 · Cited by 187 · see citing works
Phylogenetic Supermatrix Analysis of GenBank Sequences from 2228 Papilionoid Legumes
McMahon, M. M., & Sanderson, M. J. (2006) · Systematic Biology · doi:10.1080/10635150600999150 · Cited by 177 · see citing works
Does Choice in Model Selection Affect Maximum Likelihood Analysis?
Ripplinger, J., & Sullivan, J. M. (2008) · Systematic Biology · doi:10.1080/10635150801898920 · Cited by 145 · see citing works
Exploring New Search Algorithms and Hardware for Phylogenetics: RAxML Meets the IBM Cell
Stamatakis, A., Blagojević, F., Nikolopoulos, D. S., & Antonopoulos, C. D. (2007) · The Journal of VLSI Signal Processing Systems for Signal Image and Video Technology · doi:10.1007/s11265-007-0067-4 · Cited by 141 · see citing works
Self-citationRAxML-OMP: An Efficient Program for Phylogenetic Inference on SMPs
Stamatakis, A., Ott, M., & Ludwig, T. G. (2005) · Lecture notes in computer science · doi:10.1007/11535294_25 · Cited by 138 · see citing works
Self-citationLarge-scale maximum likelihood-based phylogenetic analysis on the IBM BlueGene/L
Ott, M., Żola, J., Stamatakis, A., & Aluru, S. (2007) · ACM/IEEE Conference on Supercomputing (SC) · doi:10.1145/1362622.1362628 · Cited by 136 · see citing works
Self-citationThe memory gap and the future of high performance memories
Wilkes, M. V. (2001) · ACM SIGARCH Computer Architecture News · doi:10.1145/373574.373576 · Cited by 106 · see citing works
Maximum likelihood of evolutionary trees: hardness and approximation
Chor, B., & Tuller, T. (2005) · Bioinformatics · doi:10.1093/bioinformatics/bti1027 · Cited by 96 · see citing works
pIQPNNI: parallel reconstruction of large maximum likelihood phylogenies
Minh, B. Q., Le, V. S., von Haeseler, A., & Schmidt, H. A. (2005) · Computer applications in the biosciences · doi:10.1093/bioinformatics/bti594 · Cited by 82 · see citing works
Initial Experiences Porting a Bioinformatics Application to a Graphics Processor
Charalambous, M., Trancoso, P., & Stamatakis, A. (2005) · Lecture notes in computer science · doi:10.1007/11573036_39 · Cited by 77 · see citing works
Self-citationDynamic multigrain parallelization on the cell broadband engine
Blagojević, F., Nikolopoulos, D. S., Stamatakis, A., et al. (2007) · ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming · doi:10.1145/1229428.1229445 · Cited by 77 · see citing works
Self-citationGrimm, G. W., Renner, S. S., Stamatakis, A., et al. (2006) · PubMed · doi:10.5282/ubm/epub.14646 · Cited by 75 · see citing works
Self-citationTowards a discipline of experimental algorithmics
Moret, B. M. E. (2002) · DIMACS series in discrete mathematics and theoretical computer science · doi:10.1090/dimacs/059/10 · Cited by 74 · see citing works
MultiPhyl: a high-throughput phylogenomics webserver using distributed computing
Keane, T., Naughton, T. J., & McInerney, J. O. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm359 · Cited by 73 · see citing works
Morrison, D. A. (2007) · Systematic Biology · doi:10.1080/10635150701779808 · Cited by 65 · see citing works
Goldwasser, M. H., Johnson, D., & McGeoch, C. C. (2002) · DIMACS series in discrete mathematics and theoretical computer science · doi:10.1090/dimacs/059 · Cited by 62 · see citing works
DPRml: distributed phylogeny reconstruction by maximum likelihood
Keane, T., Naughton, T. J., Travers, S. A. A., et al. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bti100 · Cited by 59 · see citing works
Phylemon: a suite of web tools for molecular evolution, phylogenetics and phylogenomics
Tárraga, J., Medina, I., Arbiza, L., Huerta‐Cepas, J., Gabaldón, T., Dopazo, J., & Dopazo, H. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm224 · Cited by 49 · see citing works
Waddell, P. J., Kishino, H., & Ota, R. (2002) · PubMed · Cited by 44 · see citing works
PHY·FI: fast and easy online creation and manipulation of phylogeny color figures
Fredslund, J. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-315 · Cited by 40 · see citing works
Whelan, S. (2007) · Systematic Biology · doi:10.1080/10635150701611134 · Cited by 34 · see citing works
PhyNav: A Novel Approach to Reconstruct Large Phylogenies
Vinh, S. L., Schmidt, H. A., & von Haeseler, A. (2005) · Studies in classification, data analysis, and knowledge organization · doi:10.1007/3-540-28084-7_44 · Cited by 12 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies
Stamatakis, A. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu033 · Cited by 32,291 · see citing works
Self-citationGuindon, S., Dufayard, J.-F., Lefort, V., Anisimova, M., Hordijk, W., & Gascuel, O. (2010) · Systematic Biology · doi:10.1093/sysbio/syq010 · Cited by 18,376 · see citing works
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 · see citing works
UFBoot2: Improving the Ultrafast Bootstrap Approximation
Hoang, D. T., Chernomor, O., von Haeseler, A., Minh, B. Q., & Vinh, L. S. (2018) · Molecular Biology and Evolution · doi:10.1093/molbev/msx281 · Cited by 10,881 · see citing works
Ultrafast Approximation for Phylogenetic Bootstrap
Minh, B. Q., Nguyen, M. A. T., & von Haeseler, A. (2013) · Molecular Biology and Evolution · doi:10.1093/molbev/mst024 · Cited by 4,844 · see citing works
Host and viral traits predict zoonotic spillover from mammals
Olival, K. J., Hosseini, P. R., Zambrana-Torrelio, C., Ross, N., Bogich, T. L., & Daszak, P. (2017) · Nature · doi:10.1038/nature22975 · Cited by 1,130 · see citing works
Chemical phylogenetics of histone deacetylases
Bradner, J. E., West, N., Grachan, M. L., Greenberg, E. F., Haggarty, S. J., Warnow, T., & Mazitschek, R. (2010) · Nature Chemical Biology · doi:10.1038/nchembio.313 · Cited by 720 · see citing works
The oral microbiome and the immunobiology of periodontal disease and caries
Costalonga, M., & Herzberg, M. C. (2014) · Immunology Letters · doi:10.1016/j.imlet.2014.08.017 · Cited by 645 · see citing works
Adler, C. J., Dobney, K., Weyrich, L. S., Kaidonis, J., Walker, A. W., Haak, W., Bradshaw, C. J. A., Townsend, G., Sołtysiak, A., Alt, K. W., et al. (2013) · Nature Genetics · doi:10.1038/ng.2536 · Cited by 621 · see citing works
Contentious relationships in phylogenomic studies can be driven by a handful of genes
Shen, X.-X., Hittinger, C. T., & Rokas, A. (2017) · Nature Ecology & Evolution · doi:10.1038/s41559-017-0126 · Cited by 520 · see citing works
Intestinal microbiota associated with differential feed conversion efficiency in chickens
Stanley, D., Denman, S. E., Hughes, R. J., Geier, M. S., Crowley, T. M., Chen, H., Haring, V. R., & Moore, R. J. (2012) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-011-3847-5 · Cited by 312 · see citing works
Auxin-related gene families in abiotic stress response in Sorghum bicolor
Wang, S., Bai, Y., Shen, C., Wu, Y., Zhang, S., Jiang, D., Guilfoyle, T. J., Chen, M., & Qi, Y. (2010) · Functional & Integrative Genomics · doi:10.1007/s10142-010-0174-3 · Cited by 297 · see citing works
Riesgo, A., Farrar, N., Windsor, P. J., Giribet, G., & Leys, S. P. (2014) · Molecular Biology and Evolution · doi:10.1093/molbev/msu057 · Cited by 266 · see citing works
Fleming’s penicillin producing strain is not Penicillium chrysogenum but P. rubens
Houbraken, J., Frisvad, J. C., & Samson, R. A. (2011) · IMA Fungus · doi:10.5598/imafungus.2011.02.01.12 · Cited by 262 · see citing works
Schierwater, B., Eitel, M., Jakob, W., Osigus, H.-J., Hadrys, H., Dellaporta, S. L., Kolokotronis, S.-O., & DeSalle, R. (2009) · PLoS Biology · doi:10.1371/journal.pbio.1000020 · Cited by 260 · see citing works
Using RAxML to infer phylogenies
Stamatakis, A. (2015) · Current Protocols in Bioinformatics · doi:10.1002/0471250953.bi0614s51 · Cited by 243 · see citing works
Self-citationRAxML and FastTree: comparing two methods for large-scale maximum likelihood phylogeny estimation
Liu, K., Linder, C. R., & Warnow, T. (2011) · PLoS ONE · doi:10.1371/journal.pone.0027731 · Cited by 207 · see citing works
The cytochrome P450 genesis locus: the origin and evolution of animal cytochrome P450s
Nelson, D. R., Goldstone, J. V., & Stegeman, J. J. (2013) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2012.0474 · Cited by 193 · see citing works
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Lindqvist, C., Schuster, S. C., Sun, Y., Talbot, S. L., Qi, J., Ratan, A., Tomsho, L. P., Kasson, L., Zeyl, E., Aars, J., et al. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0914266107 · Cited by 193 · see citing works
Constant, P., Chowdhury, S. P., Pratscher, J., & Conrad, R. (2010) · Environmental Microbiology · doi:10.1111/j.1462-2920.2009.02130.x · Cited by 171 · see citing works
Extensive loss of cell-cycle and DNA repair genes in an ancient lineage of bipolar budding yeasts
Steenwyk, J. L., Opulente, D. A., Kominek, J., Shen, X.-X., Zhou, X., Labella, A. L., Bradley, N. P., Eichman, B. F., Čadež, N., Libkind, D., et al. (2019) · PLoS Biology · doi:10.1371/journal.pbio.3000255 · Cited by 162 · see citing works
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Gold, D. A., Grabenstatter, J., de Mendoza, A., Riesgo, A., Ruiz-Trillo, I., & Summons, R. E. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1512614113 · Cited by 145 · see citing works
Clark, G. B., Morgan, R. O., Fernandez, M., & Roux, S. J. (2012) · New Phytologist · doi:10.1111/j.1469-8137.2012.04308.x · Cited by 150 · see citing works
Losasso, C., Eckert, E. M., Mastrorilli, E., Villiger, J., Mancin, M., Patuzzi, I., Di Cesare, A., Cibin, V., Barrucci, F., Pernthaler, J., et al. (2018) · Frontiers in Microbiology · doi:10.3389/fmicb.2018.00317 · Cited by 125 · see citing works
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Mitogenomics at the base of Metazoa
Osigus, H.-J., Eitel, M., Bernt, M., Donath, A., & Schierwater, B. (2013) · Molecular Phylogenetics and Evolution · doi:10.1016/j.ympev.2013.07.016 · Cited by 89 · see citing works
Detecting the symplesiomorphy trap: A multigene phylogenetic analysis of terebelliform annelids
Zhong, M., Hansen, B., Nesnidal, M., Golombek, A., Halanych, K. M., & Struck, T. H. (2011) · BMC Evolutionary Biology · doi:10.1186/1471-2148-11-369 · Cited by 73 · see citing works
Suzuki, S., Ishii, S., Hoshino, T., Rietze, A., Tenney, A., Morrill, P. L., Inagaki, F., Kuenen, J. G., & Nealson, K. H. (2017) · The ISME Journal · doi:10.1038/ismej.2017.111 · Cited by 78 · see citing works
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Nesnidal, M. P., Helmkampf, M., Bruchhaus, I., El-Matbouli, M., & Hausdorf, B. (2013) · PLoS ONE · doi:10.1371/journal.pone.0054576 · Cited by 64 · see citing works
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Adler, C. J., Malik, R., Browne, G. V., & Norris, J. M. (2016) · Microbiome · doi:10.1186/s40168-016-0169-y · Cited by 65 · see citing works
Durham, B. P., Grote, J., Whittaker, K. A., Bender, S. J., Luo, H., Grim, S. L., Brown, J. M., Casey, J. R., Dron, A., Florez-Leiva, L., et al. (2014) · Standards in Genomic Sciences · doi:10.4056/sigs.4998989 · Cited by 62 · see citing works
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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 · see citing works
Stampar, S. N., Maronna, M. M., Vermeij, M. J. A., Silveira, F. L. D., & Morandini, A. C. (2012) · PLoS ONE · doi:10.1371/journal.pone.0041091 · Cited by 50 · see citing works
Ekman, S., & Blaalid, R. (2011) · Systematic Biology · doi:10.1093/sysbio/syr022 · Cited by 51 · see citing works
Maltsev, Y., Krivova, Z., Maltseva, S., Maltseva, K., Gorshkova, E., & Kulikovskiy, M. (2021) · Scientific Reports · doi:10.1038/s41598-021-99376-9 · Cited by 40 · see citing works
Interrelationships of chromalveolates within a broadly sampled tree of photosynthetic protists
Reeb, V. C., Peglar, M. T., Yoon, H. S., Bai, J. R., Wu, M., Shiu, P., Grafenberg, J. L., Reyes-Prieto, A., Rümmele, S. E., & Gross, J. (2009) · Molecular Phylogenetics and Evolution · doi:10.1016/j.ympev.2009.04.012 · Cited by 35 · see citing works
Suzuki, S., Nealson, K. H., & Ishii, S. (2018) · Frontiers in Microbiology · doi:10.3389/fmicb.2018.03141 · Cited by 36 · see citing works
Maltsev, Y., Maltseva, I., Maltseva, S., Kociolek, J. P., & Kulikovskiy, M. (2021) · Journal of Phycology · doi:10.1111/jpy.13116 · Cited by 31 · see citing works
Maltsev, Y., Gusev, E., Maltseva, I., Kulikovskiy, M., Namsaraev, Z., Petrushkina, M., Filimonova, A., Sorokin, B., Golubeva, A., Butaeva, G., et al. (2018) · Algal Research · doi:10.1016/j.algal.2018.06.008 · Cited by 29 · see citing works
Maltsev, Y., Maltseva, I., Maltseva, S., Kociolek, J. P., & Kulikovskiy, M. (2019) · Journal of Phycology · doi:10.1111/jpy.12903 · Cited by 28 · see citing works
Gizachew, S., & Engidawork, E. (2024) · Genes · doi:10.3390/genes15111389 · Cited by 15 · see citing works
“The support values in the system are generated using 100 rounds of the “Rapid” bootstrapping option [28] of RAxML (8.2.11).”
Influentialda Silva, T. F., Glória, R. D. A., de Sousa, T. J., Americo, M. F., Freitas, A. D. S., Viana, M. V. C., de Jesus, L. C. L., da Silva Prado, L. C., Daniel, N., Ménard, O., et al. (2023) · BMC Microbiology · doi:10.1186/s12866-023-03112-4 · Cited by 11 · see citing works
- Authors
- Stamatakis, A., Hoover, P., & Rougemont, J.
- Affiliations
- Ludwig-Maximilians-Universität München (DE)
- San Diego Supercomputer Center (US)
- École Polytechnique Fédérale de Lausanne (CH)
- Corresponding author
- Stamatakis, Alexandros
- Venue
- Systematic Biology
- Publisher
- Oxford University Press (OUP)
- Published
- 2008-10-01
- Volume
- 57
- Issue
- 5
- Pages
- 758-771
- ISSN
- 1063-5157 (ISSN-L)
- 1076-836X
- OpenAlex
- W2127847431
- Cited by
- 7,028
- References
- 44
- Citations by year
- 2026: 98 · 2025: 166 · 2024: 239 · 2023: 260 · 2022: 274 · 2021: 349 · 2020: 393 · 2019: 426 · 2018: 466 · 2017: 496 · 2016: 520 · 2015: 543 · 2014: 594 · 2013: 605 · 2012: 521
- FWCI
- 145.65
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Systematic Biology (publishedVersion)
- PubMed (publishedVersion)
- reroDoc Digital Library (submittedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
- 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
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fractal and DNA sequence analysis
- Keywords
- bootstrap support, RAxML, maximum likelihood phylogeny, web server, high-performance computing, Robinson-Foulds distance, consensus trees
- MeSH terms
- Algorithms, Computers, Phylogeny, Plants, Software, Likelihood Functions, Evolution, Molecular, Internet
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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 ›
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