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FastTree 2 – Approximately Maximum-Likelihood Trees for Large Alignments
Open accessAbstract
BACKGROUND: We recently described FastTree, a tool for inferring phylogenies for alignments with up to hundreds of thousands of sequences. Here, we describe improvements to FastTree that improve its accuracy without sacrificing scalability. METHODOLOGY/PRINCIPAL FINDINGS: Where FastTree 1 used nearest-neighbor interchanges (NNIs) and the minimum-evolution criterion to improve the tree, FastTree 2 adds minimum-evolution subtree-pruning-regrafting (SPRs) and maximum-likelihood NNIs. FastTree 2 uses heuristics to restrict the search for better trees and estimates a rate of evolution for each site (the "CAT" approximation). Nevertheless, for both simulated and genuine alignments, FastTree 2 is slightly more accurate than a standard implementation of maximum-likelihood NNIs (PhyML 3 with default settings). Although FastTree 2 is not quite as accurate as methods that use maximum-likelihood SPRs, most of the splits that disagree are poorly supported, and for large alignments, FastTree 2 is 100-1,000 times faster. FastTree 2 inferred a topology and likelihood-based local support values for 237,882 distinct 16S ribosomal RNAs on a desktop computer in 22 hours and 5.8 gigabytes of memory. CONCLUSIONS/SIGNIFICANCE: FastTree 2 allows the inference of maximum-likelihood phylogenies for huge alignments. FastTree 2 is freely available at http://www.microbesonline.org/fasttree.
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![Figure 1 Local support values for splits found by PhyML with SPR moves and/or FastTree. We examined local support values for the splits inferred by PhyML 3.0 with + SPRs on simulated alignments with 250 protein sequences. We classified PhyML's splits as correct and found by both PhyML and FastTree, correct but missed by FastTree, or incorrect. We show the distribution of support values for each class. The right-most bin includes the strongly supported splits (0.95 to 1.0), and the gray dashed line shows the uniform distribution. The support values are PhyML's minimum of the approximate likelihood ratio test [21] and SH-like [16], [17] local supports.](/paper-figures/8d86db71595b4c3189b248ede78bcc3f/fasttree-2-approximately-maximum-likelihood-trees-for-large-alignments-figure-1.jpg)
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“Thus, the validation process for our methods is centered around the comparison of phylogenetic trees estimated from the alignment with FastTree 2.1 (ref. 34).”
From Improving microbial phylogeny with citizen science within a mass-market video game (2025) · cites this paper as [34]
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 Price 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 Price et al. 2010
In the citing paper
“As a tradeoff, FastTree generates less accurate tree estimates than SPR-based ML methods (Price et al. 2010).”
From Evaluating fast maximum likelihood-based phylogenetic programs using empirical phylogenomic data sets (2018) · cites this paper as Price et al. 2010
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“For example, the recently developed FastTree program can be orders of magnitude faster than either PhyML or RAxML/ExaML (Price et al. 2010).”
From Evaluating fast maximum likelihood-based phylogenetic programs using empirical phylogenomic data sets (2018) · cites this paper as Price et al. 2010
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Cites
The neighbor-joining method: a new method for reconstructing phylogenetic trees.
Saitou, N., & Nei, M. (1987) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a040454 · Cited by 59,959
CONFIDENCE 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
DeLong, E. R., DeLong, D. M., & Clarke-Pearson, D. L. (1988) · Biometrics · doi:10.2307/2531595 · Cited by 22,649
Guindon, S., Dufayard, J.-F., Lefort, V., Anisimova, M., Hordijk, W., & Gascuel, O. (2010) · Systematic Biology · doi:10.1093/sysbio/syq010 · Cited by 18,376
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
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
Evolutionary trees from DNA sequences: A maximum likelihood approach.
Felsenstein, J. (1981) · Journal of Molecular Evolution · doi:10.1007/bf01734359 · Cited by 14,571
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
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
FastTree: Computing Large Minimum Evolution Trees with Profiles instead of a Distance Matrix
Price, M. N., Dehal, P. S., & Arkin, A. P. (2009) · Molecular Biology and Evolution · doi:10.1093/molbev/msp077 · Cited by 5,602
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Walker, M. C., Eslami, S. M., Hetrick, K. J., Ackenhusen, S. E., Mitchell, D. A., & van der Donk, W. A. (2020) · BMC Genomics · doi:10.1186/s12864-020-06785-7 · Cited by 149
Resolving the structure of phage–bacteria interactions in the context of natural diversity
Kauffman, K. M., Chang, W. K., Brown, J. M., Hussain, F. A., Yang, J., Polz, M. F., & Kelly, L. (2022) · Nature Communications · doi:10.1038/s41467-021-27583-z · Cited by 149
Davis, G. S., Waits, K., Nordstrom, L., Weaver, B., Aziz, M., Gauld, L., Grande, H., Bigler, R., Horwinski, J., Porter, S. B., et al. (2015) · Clinical Infectious Diseases · doi:10.1093/cid/civ428 · Cited by 148
Convergent Bacterial Microbiotas in the Fungal Agricultural Systems of Insects
Aylward, F. O., Suen, G., Biedermann, P. H. W., Adams, A. S., Scott, J. J., Malfatti, S., del Rio, T. G., Tringe, S. G., Poulsen, M., Raffa, K. F., et al. (2014) · mBio · doi:10.1128/mbio.02077-14 · Cited by 148
Development of the Preterm Gut Microbiome in Twins at Risk of Necrotising Enterocolitis and Sepsis
Stewart, C. J., Marrs, E. C. L., Nelson, A., Lanyon, C. V., Perry, J. D., Embleton, N. D., Cummings, S. P., & Berrington, J. E. (2013) · PLoS ONE · doi:10.1371/journal.pone.0073465 · Cited by 148
Mechanism of tetracycline resistance by ribosomal protection protein Tet(O)
Li, W., Atkinson, G. C., Thakor, N. S., Allas, Ü., Lu, C.-C., Chan, K.-Y., Tenson, T., Schulten, K., Wilson, K. S., Hauryliuk, V., et al. (2013) · Nature Communications · doi:10.1038/ncomms2470 · Cited by 147
Cheng, Y., Tan, G., Zhu, Q., Wang, C., Ruan, G., Ying, S., Qie, J., Hu, X., Xiao, Z., Xu, F., et al. (2023) · Gut Microbes · doi:10.1080/19490976.2023.2284247 · Cited by 147
Long, S. W., Olsen, R. J., Eagar, T. N., Beres, S. B., Zhao, P., Davis, J. J., Brettin, T. S., Xia, F., & Musser, J. M. (2017) · mBio · doi:10.1128/mbio.00489-17 · Cited by 147
Buelow, E., Bayjanov, J. R., Majoor, E. A. M., Willems, R. J. L., Bonten, M. J. M., Schmitt, H., & van Schaik, W. (2018) · FEMS Microbiology Ecology · doi:10.1093/femsec/fiy087 · Cited by 147
Kong, W., Wei, X., Wu, Y., Shao, M., Zhang, Q., Sadowsky, M. J., Ishii, S., Reich, P. B., Wei, G., Jiao, S., et al. (2022) · Global Change Biology · doi:10.1111/gcb.16334 · Cited by 147
Population-level impacts of antibiotic usage on the human gut microbiome
Lee, K., Raguideau, S., Sirén, K., Asnicar, F., Cumbo, F., Hildebrand, F., Segata, N., Cha, C., & Quince, C. (2023) · Nature Communications · doi:10.1038/s41467-023-36633-7 · Cited by 147
Bacterial communities associated with four ctenophore genera from the German Bight (North Sea)
Hao, W., Gerdts, G., Peplies, J., & Wichels, A. (2014) · FEMS Microbiology Ecology · doi:10.1093/femsec/fiu006 · Cited by 146
Werner, J. J., García, M. L., Perkins, S. D., Yarasheski, K. E., Smith, S. R., Muegge, B. D., Stadermann, F. J., DeRito, C. M., Floss, C., Madsen, E. L., et al. (2014) · Applied and Environmental Microbiology · doi:10.1128/aem.00166-14 · Cited by 146
Mullins, A. J., Murray, J. A. H., Bull, M. J., Jenner, M., Jones, C., Webster, G., Green, A. E., Neill, D. R., Connor, T. R., Parkhill, J., et al. (2019) · Nature Microbiology · doi:10.1038/s41564-019-0383-z · Cited by 146
Alba, P., Leekitcharoenphon, P., Carfora, V., Amoruso, R., Cordaro, G., Matteo, P. D., Ianzano, A., Iurescia, M., Diaconu, E. L., ENGAGE-EURL-AR Network Study Group, et al. (2020) · Microbial Genomics · doi:10.1099/mgen.0.000365 · Cited by 146
Regueira‐Iglesias, A., Balsa‐Castro, C., Blanco‐Pintos, T., & Tomás, I. (2023) · Molecular Oral Microbiology · doi:10.1111/omi.12434 · Cited by 146
A widespread coral-infecting apicomplexan with chlorophyll biosynthesis genes
Kwong, W. K., del Campo, J., Mathur, V., Vermeij, M. J. A., & Keeling, P. J. (2019) · Nature · doi:10.1038/s41586-019-1072-z · Cited by 145
Light-driven anaerobic microbial oxidation of manganese
Daye, M., Klepac-Ceraj, V., Pajusalu, M., Rowland, S., Farrell-Sherman, A., Beukes, N., Tamura, N., Fournier, G., & Bosak, T. (2019) · Nature · doi:10.1038/s41586-019-1804-0 · Cited by 145
Kim, Y. S., Kim, J., & Park, S.-J. (2015) · Anaerobe · doi:10.1016/j.anaerobe.2015.01.004 · Cited by 145
From Rare to Dominant: a Fine-Tuned Soil Bacterial Bloom during Petroleum Hydrocarbon Bioremediation
Fuentes-Alburquenque, S., Barra-Sanhueza, B., Caporaso, J. G., & Seeger, M. (2015) · Applied and Environmental Microbiology · doi:10.1128/aem.02625-15 · Cited by 145
The digestive and defensive basis of carcass utilization by the burying beetle and its microbiota
Vogel, H., Shukla, S. P., Engl, T., Weiß, B., Fischer, R., Steiger, S., Heckel, D. G., Kaltenpoth, M., & Vilcinskas, A. (2017) · Nature Communications · doi:10.1038/ncomms15186 · Cited by 145
Host-associated microbiomes are predicted by immune system complexity and climate
Woodhams, D. C., Bletz, M. C., Becker, C. G., Bender, H. A., Buitrago-Rosas, D., Diebboll, H., Huynh, R., Kearns, P. J., Kueneman, J. G., Kurosawa, E., et al. (2020) · Genome biology · doi:10.1186/s13059-019-1908-8 · Cited by 145
Long, S. W., Olsen, R. J., Christensen, P. A., Bernard, D. W., Davis, J. J., Shukla, M. P., Nguyen, M., Saavedra, M. O., Yerramilli, P., Pruitt, L., et al. (2020) · mBio · doi:10.1128/mbio.02707-20 · Cited by 145
Kochan, T. J., Nozick, S., Valdes, A., Mitra, S. D., Cheung, B. H., Lebrun-Corbin, M., Medernach, R. L., Vessely, M., Mills, J. O., Axline, C. M. R., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-43802-1 · Cited by 145
McGaughey, K. D., Yilmaz-Swenson, T., Elsayed, N. M., Cruz, D. A., Rodriguiz, R. M., Kritzer, M. D., Peterchev, A. V., Roach, J. M., Wetsel, W. C., & Williamson, D. E. (2019) · Scientific Reports · doi:10.1038/s41598-019-40140-5 · Cited by 145
Genome streamlining and chemical defense in a coral reef symbiosis
Kwan, J. C., Donia, M. S., Han, A., Hirose, E., Haygood, M. G., & Schmidt, E. W. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1213820109 · Cited by 144
Kumar, N., Lad, G. R., Giuntini, E., Kaye, M., Udomwong, P., Shamsani, N. J., Young, J. P. W., & Bailly, X. (2015) · Open Biology · doi:10.1098/rsob.140133 · Cited by 144
Giant Viruses of Amoebas: An Update
Aherfi, S., Colson, P., Scola, B. L., & Raoult, D. (2016) · Frontiers in Microbiology · doi:10.3389/fmicb.2016.00349 · Cited by 144
The Potential of Class II Bacteriocins to Modify Gut Microbiota to Improve Host Health
Umu, Ö. C. O., Bäuerl, C., Oostindjer, M., Pope, P. B., Hernández, P. E., Pérez‐Martínez, G., & Diep, D. B. (2016) · PLoS ONE · doi:10.1371/journal.pone.0164036 · Cited by 144
Testing for Polytomies in Phylogenetic Species Trees Using Quartet Frequencies
Sayyari, E., & Mirarab, S. (2018) · Genes · doi:10.3390/genes9030132 · Cited by 144
Widespread horizontal transfer of retrotransposons
Walsh, A. M., Kortschak, R. D., Gardner, M., Bertozzi, T., & Adelson, D. L. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1205856110 · Cited by 143
Stop codon reassignments in the wild
Ivanova, N., Schwientek, P., Tripp, H. J., Rinke, C., Pati, A., Huntemann, M., Visel, A., Woyke, T., Kyrpides, N. C., & Rubin, E. M. (2014) · Science · doi:10.1126/science.1250691 · Cited by 143
Méric, G., Yahara, K., Mageiros, L., Pascoe, B., Maiden, M. C. J., Jolley, K. A., & Sheppard, S. K. (2014) · PLoS ONE · doi:10.1371/journal.pone.0092798 · Cited by 143
Municipal Solid Waste Landfills Harbor Distinct Microbiomes
Stamps, B. W., Lyles, C. N., Suflita, J. M., Masoner, J. R., Cozzarelli, I. M., Kolpin, D. W., & Stevenson, B. S. (2016) · Frontiers in Microbiology · doi:10.3389/fmicb.2016.00534 · Cited by 143
Energy and carbon metabolisms in a deep terrestrial subsurface fluid microbial community
Momper, L., Jungbluth, S. P., Lee, M., & Amend, J. P. (2017) · The ISME Journal · doi:10.1038/ismej.2017.94 · Cited by 143
Effects of host species and environment on the skin microbiome of Plethodontid salamanders
Muletz‐Wolz, C. R., Yarwood, S. A., Grant, E. H. C., Fleischer, R. C., & Lips, K. R. (2017) · Journal of Animal Ecology · doi:10.1111/1365-2656.12726 · Cited by 143
Compensatory evolution drives multidrug-resistant tuberculosis in Central Asia
Merker, M., Barbier, M., Cox, H. S., Rasigade, J., Feuerriegel, S., Kohl, T. A., Diel, R., Borrell, S., Gagneux, S., Nikolayevskyy, V., et al. (2018) · eLife · doi:10.7554/elife.38200 · Cited by 143
Biology and genome of a newly discovered sibling species of Caenorhabditis elegans
Kanzaki, N., Tsai, I. J., Tanaka, R., Hunt, V. L., Liu, D., Tsuyama, K., Maeda, Y., Namai, S., Kumagai, R., Tracey, A., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-05712-5 · Cited by 143
Louati, I., Pascault, N., Debroas, D., Bernard, C., Humbert, J. F., & Leloup, J. (2015) · PLoS ONE · doi:10.1371/journal.pone.0140614 · Cited by 143
The Natural History of ADP-Ribosyltransferases and the ADP-Ribosylation System
Aravind, L., Zhang, D., de Souza, R. F., Anand, S., & Iyer, L. M. (2014) · Current topics in microbiology and immunology · doi:10.1007/82_2014_414 · Cited by 142
Ultra-large alignments using phylogeny-aware profiles
Nguyen, N., Mirarab, S., Kumar, K., & Warnow, T. J. (2015) · Genome biology · doi:10.1186/s13059-015-0688-z · Cited by 142
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Sharon, I., Battchikova, N., Aro, E., Giglione, C., Meinnel, T., Glaser, F., Pinter, R. Y., Breitbart, M., Rohwer, F. L., & Béjà, O. (2011) · The ISME Journal · doi:10.1038/ismej.2011.2 · Cited by 142
Veenstra, J. A. (2014) · Frontiers in Physiology · doi:10.3389/fphys.2014.00454 · Cited by 142
Mueller, N. T., Shin, H., Pizoni, A., Werlang, I. C. R., Matte, Ú. D. S., Goldani, M. Z., Goldani, H. A. S., & Domínguez-Bello, M. G. (2016) · Scientific Reports · doi:10.1038/srep23133 · Cited by 142
Detecting and Analyzing Genetic Recombination Using RDP4
Martin, D. P., Murrell, B., Khoosal, A., & Muhire, B. M. (2016) · Methods in molecular biology · doi:10.1007/978-1-4939-6622-6_17 · Cited by 142
Biostimulation of carbonate precipitation process in soil for copper immobilization
Chen, X., & Achal, V. (2019) · Journal of Hazardous Materials · doi:10.1016/j.jhazmat.2019.01.108 · Cited by 142
Shakya, M., Ahmed, S. A., Davenport, K. W., Flynn, M., Lo, C., & Chain, P. (2020) · Scientific Reports · doi:10.1038/s41598-020-58356-1 · Cited by 142
Yuan, L., Wang, Y., Zhang, L., Palomo, A., Zhou, J. Z., Smets, B. F., Bürgmann, H., & Ju, F. (2021) · Environmental Science & Technology · doi:10.1021/acs.est.1c02483 · Cited by 142
Syringyl lignin biosynthesis is directly regulated by a secondary cell wall master switch
Zhao, Q. L., Wang, H., Yin, Y., Xu, Y., Chen, F., & Dixon, R. A. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1009170107 · Cited by 141
Lamichhaney, S., Fuentes‐Pardo, A. P., Rafati, N., Ryman, N., McCracken, G. R., Bourne, C. M., Singh, R., Ruzzante, D. E., & Andersson, L. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1617728114 · Cited by 141
Biological and phylogenetic characteristics of West African lineages of West Nile virus
Fall, G., Paola, N. D., Faye, M., Dia, M., Freire, C. C. D. M., Loucoubar, C., Zanotto, P. M. D. A., Faye, O., & Sall, A. A. (2017) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0006078 · Cited by 141
Weinroth, M. D., Belk, A. D., Dean, C. J., Noyes, N. R., Dittoe, D. K., Rothrock, M. J., Ricke, S. C., Myer, P. R., Henniger, M. T., Ramírez, G. A., et al. (2022) · Journal of Animal Science · doi:10.1093/jas/skab346 · Cited by 141
MBPD: A multiple bacterial pathogen detection pipeline for One Health practices
Yang, X., Jiang, G., Zhang, Y., Wang, N., Zhang, Y., Wang, X., Zhao, F. J., Xu, Y., Shen, Q., & Wei, Z. (2023) · iMeta · doi:10.1002/imt2.82 · Cited by 141
Quick, J., Cumley, N., Wearn, C. M., Niebel, M. O., Constantinidou, C., Thomas, C. M., Pallen, M. J., Moiemen, N. S., Bamford, A. L., Oppenheim, B. A., et al. (2014) · BMJ Open · doi:10.1136/bmjopen-2014-006278 · Cited by 140
Strategies to improve reference databases for soil microbiomes
Choi, J., Yang, F., Stepanauskas, R., Cardenas, E., Garoutte, A., Williams, R. J., Flater, J. S., Tiedje, J. M., Hofmockel, K., Gelder, B., et al. (2016) · The ISME Journal · doi:10.1038/ismej.2016.168 · Cited by 140
Frequency-dependent selection in vaccine-associated pneumococcal population dynamics
Corander, J., Fraser, C., Gutmann, M. U., Arnold, B., Hanage, W. P., Bentley, S. D., Lipsitch, M., & Croucher, N. J. (2017) · Nature Ecology & Evolution · doi:10.1038/s41559-017-0337-x · Cited by 140
Relaxed Selection Limits Lifespan by Increasing Mutation Load
Cui, R., Medeiros, T., Willemsen, D., Iasi, L. N. M., Collier, G. E., Graef, M., Reichard, M., & Valenzano, D. R. (2019) · Cell · doi:10.1016/j.cell.2019.06.004 · Cited by 140
Zhang, X., Peng, H., Zhu, S., Xing, J., Li, X., Zhu, Z., Zheng, J., Wang, L., Wang, B., Chen, J., et al. (2020) · Molecular Plant · doi:10.1016/j.molp.2020.08.014 · Cited by 140
The impact of genetic diversity on gene essentiality within the Escherichia coli species
Rousset, F., Cabezas-Caballero, J., Piastra-Facon, F., Fernández-Rodríguez, J., Clermont, O., Denamur, É., Rocha, E. P. C., & Bikard, D. (2021) · Nature Microbiology · doi:10.1038/s41564-020-00839-y · Cited by 140
The pleiotropic effects of prebiotic galacto-oligosaccharides on the aging gut
Arnold, J. W., Roach, J. M., Fabela, S., Moorfield, E., Ding, S., Blue, E., Dagher, S. F., Magness, S. T., Tamayo, R., Bruno-Bárcena, J. M., et al. (2021) · Microbiome · doi:10.1186/s40168-020-00980-0 · Cited by 140
Zhong, Y., Sorensen, P. O., Zhu, G., Jia, X., Liu, J., Shangguan, Z., Wang, R., & Yan, W. (2022) · iMeta · doi:10.1002/imt2.18 · Cited by 140
Human and rat gut microbiome composition is maintained following sleep restriction
Zhang, S. L., Bai, L., Goel, N., Bailey, A., Jang, C. J., Bushman, F. D., Meerlo, P., Dinges, D. F., & Sehgal, A. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1620673114 · Cited by 139
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Saary, P., Mitchell, A., & Finn, R. D. (2020) · Genome biology · doi:10.1186/s13059-020-02155-4 · Cited by 139
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Beets, I., Zels, S., Vandewyer, E., Demeulemeester, J., Caers, J., Baytemur, E., Courtney, A., Golinelli, L., Hasakioğulları, İ., Schafer, W. R., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.113058 · Cited by 139
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Li, G., Piampongsant, S., Faria, N. R., Voet, A. R. D., Pineda-Peña, A.-C., Khouri, R., Lemey, P., Vandamme, A., & Theys, K. (2015) · Retrovirology · doi:10.1186/s12977-015-0148-6 · Cited by 138
Dueholm, M. S., Andersen, K. S., McIlroy, S. J., Kristensen, J. M., Yashiro, E., Karst, S. M., Albertsen, M., & Nielsen, P. H. (2020) · mBio · doi:10.1128/mbio.01557-20 · Cited by 138
Myelin as a regulator of development of the microbiota-gut-brain axis
Keogh, C. E., Kim, D. H. J., Pusceddu, M. M., Knotts, T. A., Rabasa, G., Sladek, J. A., Hsieh, M. T., Honeycutt, M., Brust-Mascher, I., Barboza, M., et al. (2021) · Brain, Behavior, and Immunity · doi:10.1016/j.bbi.2020.11.001 · Cited by 137
Dillon, M. M., Thakur, S., Almeida, R. N. D., Wang, P. W., Weir, B. S., & Guttman, D. S. (2019) · Genome biology · doi:10.1186/s13059-018-1606-y · Cited by 137
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Barylski, J., Enault, F., Dutilh, B. E., Schuller, M. B. P., Edwards, R. A., Gillis, A., Klumpp, J., Knežević, P., Krupovìč, M., Kuhn, J. H., et al. (2019) · Systematic Biology · doi:10.1093/sysbio/syz036 · Cited by 137
The global Microcystis interactome
Cook, K. V., Li, C., Cai, H., Krumholz, L. R., Hambright, K. D., Paerl, H. W., Steffen, M. M., Wilson, A. E., Burford, M. A., Grossart, H., et al. (2019) · Limnology and Oceanography · doi:10.1002/lno.11361 · Cited by 137
Qiang, L., Cheng, J., Mirzoyan, S., Kerkhof, L. J., & Häggblom, M. M. (2021) · Environmental Science & Technology · doi:10.1021/acs.est.1c04108 · Cited by 137
Yang, L., Shen, Y., Jiang, J., Wang, X., Shao, D., Lam, M. M. C., Holt, K. E., Shao, B., Wu, C., Shen, J., et al. (2022) · Nature Food · doi:10.1038/s43016-022-00470-6 · Cited by 137
Dysbiosis in the Gut Microbiota in Patients with Inflammatory Bowel Disease during Remission
Pisani, A., Rausch, P., Bang, C., Ellul, S., Tabone, T., Cordina, C. M., Zahra, G., Franke, A., & Ellul, P. (2022) · Microbiology Spectrum · doi:10.1128/spectrum.00616-22 · Cited by 137
Iyer, L. M., Zhang, D., Burroughs, A. M., & Aravind, L. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt573 · Cited by 137
Genetic determinants of gut microbiota composition and bile acid profiles in mice
Kemis, J. H., Linke, V., Barrett, K. L., Boehm, F. J., Traeger, L. L., Keller, M. P., Rabaglia, M. E., Schueler, K. L., Stapleton, D. S., Gatti, D. M., et al. (2019) · PLOS Genetics · doi:10.1371/journal.pgen.1008073 · Cited by 136
Partner choice and fidelity stabilize coevolution in a Cretaceous-age defensive symbiosis
Kaltenpoth, M., Roeser-Mueller, K., Koehler, S., Peterson, A., Nechitaylo, T. Y., Stubblefield, J. W., Herzner, G., Seger, J., & Strohm, E. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1400457111 · Cited by 136
Phylogenomic Analysis of Spiders Reveals Nonmonophyly of Orb Weavers
Fernández, R., Hormiga, G., & Giribet, G. (2014) · Current Biology · doi:10.1016/j.cub.2014.06.035 · Cited by 136
Bel, M. V., Proost, S., Neste, C. V., Deforce, D. L. D., de Peer, Y. V., & Vandepoele, K. (2013) · Genome biology · doi:10.1186/gb-2013-14-12-r134 · Cited by 136
Naive binning improves phylogenomic analyses
Bayzid, M. S., & Warnow, T. J. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt394 · Cited by 136
Climate and edaphic controllers influence rhizosphere community assembly for a wild annual grass
Nuccio, E., Anderson‐Furgeson, J., Estera‐Molina, K., Pett‐Ridge, J., de Valpine, P., Brodie, E., & Firestone, M. K. (2016) · Ecology · doi:10.1890/15-0882.1 · Cited by 136
Liu, R., Wei, X. L., Song, W., Wang, L., Cao, J., Wu, J., Thomas, T., Jin, T., Wang, Z., Wei, W., et al. (2022) · Microbiome · doi:10.1186/s40168-022-01263-6 · Cited by 136
SAR11 lipid renovation in response to phosphate starvation
Carini, P., Mooy, B. A. S. V., Thrash, J. C., White, A., Zhao, Y., Campbell, E. O., Fredricks, H. F., & Giovannoni, S. J. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1505034112 · Cited by 135
Chiarello, M., Villéger, S., Bouvier, C., Bettarel, Y., & Bouvier, T. C. (2015) · FEMS Microbiology Ecology · doi:10.1093/femsec/fiv061 · Cited by 135
Dziallas, C., & Grossart, H. (2011) · Environmental Microbiology · doi:10.1111/j.1462-2920.2011.02479.x · Cited by 135
Arginine-rhamnosylation as new strategy to activate translation elongation factor P
Lassak, J., Keilhauer, E. C., Fürst, M. J. L. J., Wuichet, K., Gödeke, J., Starosta, A. L., Chen, J., Søgaard‐Andersen, L., Rohr, J., Wilson, D. N., et al. (2015) · Nature Chemical Biology · doi:10.1038/nchembio.1751 · Cited by 135
Shifts in diversity and function of lake bacterial communities upon glacier retreat
Peter, H., & Sommaruga, R. (2016) · The ISME Journal · doi:10.1038/ismej.2015.245 · Cited by 135
Similarities between decapod and insect neuropeptidomes
Veenstra, J. A. (2016) · PeerJ · doi:10.7717/peerj.2043 · Cited by 135
Community structure of the gut microbiota in sympatric species of wild Drosophila
Martinson, V. G., Douglas, A. E., & JAENIKE, J. R. (2017) · Ecology Letters · doi:10.1111/ele.12761 · Cited by 135
Mehrshad, M., Rodríguez‐Valera, F., Amoozegar, M. A., López‐García, P., & Ghai, R. (2017) · The ISME Journal · doi:10.1038/s41396-017-0009-5 · Cited by 135
Anti-CRISPR proteins encoded by archaeal lytic viruses inhibit subtype I-D immunity
He, F., Bhoobalan-Chitty, Y., van Eck, L., Kjeldsen, A. L., Dedola, M., Makarova, K. S., Koonin, E. V., Brodersen, D. E., & Peng, X. (2018) · Nature Microbiology · doi:10.1038/s41564-018-0120-z · Cited by 135
DSYB catalyses the key step of dimethylsulfoniopropionate biosynthesis in many phytoplankton
Curson, A. R. J., Williams, B. T., Pinchbeck, B. J., Sims, L. P., Martínez, A. B., Rivera, P. P. L., Kumaresan, D., Mercadé, E., Spurgin, L. G., Carrión, O., et al. (2018) · Nature Microbiology · doi:10.1038/s41564-018-0119-5 · Cited by 135
Virk, R. K., Jayakumar, J., Mendenhall, I. H., Moorthy, M., Lam, P., Linster, M., Lim, J. S. L., Lin, C., Oon, L. L. E., Lee, H. K., et al. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1916585116 · Cited by 135
European maize genomes highlight intraspecies variation in repeat and gene content
Haberer, G., Kamal, N. M., Bauer, E., Gundlach, H., Fischer, I., Seidel, M. A., Spannagl, M., Marcon, C., Ruban, A. S., Urbany, C., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0671-9 · Cited by 135
Xia, Z., Huang, D., Zhang, S., Wang, W., Ma, F., Wu, B., Xu, Y., Xu, B., Chen, D., Zou, M., et al. (2021) · Horticulture Research · doi:10.1038/s41438-020-00455-1 · Cited by 135
Morrow, J. L., Frommer, M., Shearman, D. C. A., & Riegler, M. (2015) · Microbial Ecology · doi:10.1007/s00248-015-0571-1 · Cited by 134
The functions of DNA methylation by CcrM in Caulobacter crescentus: a global approach
González, D., Kozdon, J. B., McAdams, H. H., Shapiro, L., & Collier, J. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1352 · Cited by 134
Phylogenomic Resolution of the Hemichordate and Echinoderm Clade
Cannon, J. T., Kocot, K. M., Waits, D. S., Weese, D., Swalla, B. J., Santos, S. R., & Halanych, K. M. (2014) · Current Biology · doi:10.1016/j.cub.2014.10.016 · Cited by 134
Recovery of a Medieval Brucella melitensis Genome Using Shotgun Metagenomics
Kay, G. L., Sergeant, M. J., Giuffra, V., Bandiera, P., Milanese, M., Bramanti, B., Bianucci, R., & Pallen, M. J. (2014) · mBio · doi:10.1128/mbio.01337-14 · Cited by 134
Best, N. B., Hartwig, T., Budka, J., Fujioka, S., Johal, G. S., Schulz, B., & Dilkes, B. P. (2016) · PLANT PHYSIOLOGY · doi:10.1104/pp.16.00399 · Cited by 134
Campbell, L., & Turner, S. R. (2017) · Frontiers in Plant Science · doi:10.3389/fpls.2017.00037 · Cited by 134
Metadata
- Authors
- Price, M. N., Dehal, P. S., & Arkin, A. P.
- Affiliations
- Lawrence Berkeley National Laboratory (US)
- Corresponding author
- Price, Morgan N.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2010-03-10
- Volume
- 5
- Issue
- 3
- Pages
- e9490
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC2835736
- OpenAlex
- W2031611770
- Cited by
- 14,894
- References
- 37
- Citations by year
- 2026: 1298 · 2025: 1543 · 2024: 1657 · 2023: 1486 · 2022: 1676 · 2021: 1651 · 2020: 1363 · 2019: 1013 · 2018: 776 · 2017: 686 · 2016: 521 · 2015: 415 · 2014: 309 · 2013: 256 · 2012: 133
- FWCI
- 63.80
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- eScholarship (California Digital Library) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- Figshare (submittedVersion, cc-by)
- Funders
- U.S. Department of Energy (-AC02-05CH11231, 05CH11231, DE AC02 05CH11231, DE-AC02-)
- 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
- phylogenetic inference, maximum likelihood phylogeny, nearest neighbor interchange, cat model, 16S rRNA, phylogenetic accuracy, scalability
- MeSH terms
- Algorithms, Animals, Computers, Data Interpretation, Statistical, Genetic Techniques, Humans, Models, Genetic, Phylogeny, RNA, Ribosomal, 16S, Software, Likelihood Functions, Sequence Alignment, Databases, Protein
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