This list of phylogenetics software is a compilation of computational phylogenetics software used to produce phylogenetic trees. Such tools are commonly used in comparative genomics, cladistics, and bioinformatics. Methods for estimating phylogenies include neighbor-joining, maximum parsimony (also simply referred to as parsimony), unweighted pair group method with arithmetic mean (UPGMA), Bayesian phylogenetic inference, maximum likelihood, and distance matrix methods.
Name | Description | Methods | Author |
---|---|---|---|
ADMIXTOOLS [1] | R software package that contains the qpGraph, qpAdm, qpWave, and qpDstat programs | Nick Patterson, David Reich | |
AncesTree [2] | An algorithm for clonal tree reconstruction from multi-sample cancer sequencing data. | Maximum Likelihood, Integer Linear Programming (ILP) | M. El-Kebir, L. Oesper, H. Acheson-Field, B. J. Raphael |
AliGROOVE [3] | Visualisation of heterogeneous sequence divergence within multiple sequence alignments and detection of inflated branch support | Identification of single taxa which show predominately randomized sequence similarity in comparison with other taxa in a multiple sequence alignment and evaluation of the reliability of node support in a given topology | Patrick Kück, Sandra A Meid, Christian Groß, Bernhard Misof, Johann Wolfgang Wägele. |
ape [4] | R-Project package for analysis of phylogenetics and evolution | Provides a large variety of phylogenetics functions | Maintainer: Emmanuel Paradis |
Armadillo Workflow Platform [5] | Workflow platform dedicated to phylogenetic and general bioinformatic analysis | Inference of phylogenetic trees using Distance, Maximum Likelihood, Maximum Parsimony, Bayesian methods and related workflows | E. Lord, M. Leclercq, A. Boc, A.B. Diallo and V. Makarenkov |
BAli-Phy [6] | Simultaneous Bayesian inference of alignment and phylogeny | Bayesian inference, alignment as well as tree search | M.A. Suchard, B. D. Redelings |
BATWING [7] | Bayesian Analysis of Trees With Internal Node Generation | Bayesian inference, demographic history, population splits | I. J. Wilson, Weale, D.Balding |
BayesPhylogenies [8] | Bayesian inference of trees using Markov chain Monte Carlo methods | Bayesian inference, multiple models, mixture model (auto-partitioning) | M. Pagel, A. Meade |
BayesTraits [9] | Analyses trait evolution among groups of species for which a phylogeny or sample of phylogenies is available | Trait analysis | M. Pagel, A. Meade |
BEAST [10] | Bayesian Evolutionary Analysis Sampling Trees | Bayesian inference, relaxed molecular clock, demographic history | A. J. Drummond, M. A. Suchard, D Xie & A. Rambaut |
BioNumerics | Universal platform for the management, storage and analysis of all types of biological data, including tree and network inference of sequence data | Neighbor-joining, maximum parsimony, UPGMA, maximum likelihood, distance matrix methods,... Calculation of the reliability of trees/branches using bootstrapping, permutation resampling or error resampling | L. Vauterin & P. Vauterin. |
Bosque | Integrated graphical software to perform phylogenetic analyses, from the importing of sequences to the plotting and graphical edition of trees and alignments | Distance and maximum likelihood methods (through PhyML, PHYLIP, Tree-Puzzle) | S. Ramirez, E. Rodriguez. |
BUCKy | Bayesian concordance of gene trees | Bayesian concordance using modified greedy consensus of unrooted quartets | C. Ané, B. Larget, D.A. Baum, S.D. Smith, A. Rokas and B. Larget, S.K. Kotha, C.N. Dewey, C. Ané |
Canopy [11] | Assessing intratumor heterogeneity and tracking longitudinal and spatial clonal evolutionary history by next-generation sequencing | Maximum Likelihood, Markov Chain Monte Carlo (MCMC) methods | Y. Jiang, Y. Qiu, A. J. Minn, and N. R. Zhang |
CGRphylo [12] | CGR method for accurate classification and tracking of rapidly evolving viruses | Chaos Game Representation (CGR) method, based on concepts of statistical physics | Amarinder Singh Thind, Somdatta Sinha |
CITUP | Clonality Inference in Tumors Using Phylogeny | Exhaustive search, Quadratic Integer Programming (QIP) | S. Malikic, A.W. McPherson, N. Donmez, C.S. Sahinalp |
ClustalW | Progressive multiple sequence alignment | Distance matrix/nearest neighbor | Thompson et al. [13] |
CoalEvol | Simulation of DNA and protein evolution along phylogenetic trees (that can also be simulated with the coalescent) | Simulation of multiple sequence alignments of DNA or protein sequences | M. Arenas, D. Posada |
CodABC | Coestimation of substitution, recombination and dN/dS in protein sequences | Approximate Bayesian computation | M. Arenas, J.S. Lopes, M.A. Beaumont, D. Posada |
Dendroscope [14] | Tool for visualizing rooted trees and calculating rooted networks | Rooted trees, tanglegrams, consensus networks, hybridization networks | Daniel Huson et al. |
EXACT [15] [16] | EXACT is based on the perfect phylogeny model, and uses a very fast homotopy algorithm to evaluate the fitness of different trees, and then it brute forces the tree search using GPUs, or multiple CPUs, on the same or on different machines | Brute force search and homotopy algorithm | Jia B., Ray S., Safavi S., Bento J. |
EzEditor [17] | EzEditor is a java-based sequence alignment editor for rRNA and protein coding genes. It allows manipulation of both DNA and protein sequence alignments for phylogenetic analysis | Neighbor Joining | Jeon, Y.S. et al. |
fastDNAml | Optimized maximum likelihood (nucleotides only) | Maximum likelihood | G.J. Olsen |
FastTree 2 [18] | Fast phylogenetic inference for alignments with up to hundreds of thousands of sequences | Approximate maximum likelihood | M.N. Price, P.S. Dehal, A.P. Arkin |
fitmodel | Fits branch-site codon models without the need of prior knowledge of clades undergoing positive selection | Maximum likelihood | S. Guindon |
Geneious | Geneious provides genome and proteome research tools | Neighbor-joining, UPGMA, MrBayes plugin, PhyML plugin, RAxML plugin, FastTree plugin, GARLi plugin, PAUP* Plugin | A. J. Drummond, M.Suchard, V.Lefort et al. |
HyPhy | Hypothesis testing using phylogenies | Maximum likelihood, neighbor-joining, clustering techniques, distance matrices | S.L. Kosakovsky Pond, S.D.W. Frost, S.V. Muse |
INDELlible [19] | Simulation of DNA/protein sequence evolution | Simulation | W. Fletcher, Z. Yang |
IQPNNI | Iterative ML treesearch with stopping rule | Maximum likelihood, neighbor-joining | L.S. Vinh, A. von Haeseler, B.Q. Minh |
IQ-Tree [20] | An efficient phylogenomic software by maximum likelihood, as successor of IQPNNI and Tree-Puzzle | Maximum likelihood, model selection, partitioning scheme finding, AIC, AICc, BIC, ultrafast bootstrapping, [21] branch tests, tree topology tests, likelihood mapping | Lam-Tung Nguyen, O. Chernomor, H.A. Schmidt, A. von Haeseler, B.Q. Minh |
jModelTest 2 | A high-performance computing program to carry out statistical selection of best-fit models of nucleotide substitution | Maximum likelihood, AIC, BIC, DT, hLTR, dLTR | D. Darriba, GL. Taboada, R. Doallo, D. Posada |
JolyTree [22] [23] | An alignment-free bioinformatics procedure to infer distance-based phylogenetic trees from genome assemblies, specifically designed to quickly infer trees from genomes belonging to the same genus | MinHash-based pairwise genome distance, Balanced Minimum Evolution (BME), ratchet-based BME tree search, Rate of Elementary Quartets | A. Criscuolo |
LisBeth | Three-item analysis for phylogenetics and biogeography | Three-item analysis | J. Ducasse, N. Cao & R. Zaragüeta-Bagils |
MEGA | Molecular Evolutionary Genetics Analysis | Distance, Parsimony and Maximum Composite Likelihood Methods | Tamura K, Dudley J, Nei M & Kumar S |
MegAlign Pro | MegAlign Pro is part of DNASTAR's Lasergene Molecular Biology package. This application performs multiple and pairwise sequence alignments, provides alignment editing, and generates phylogenetic trees. | Maximum Likelihood (RAxML) and Neighbor-Joining | DNASTAR |
Mesquite | Mesquite is software for evolutionary biology, designed to help biologists analyze comparative data about organisms. Its emphasis is on phylogenetic analysis, but some of its modules concern comparative analyses or population genetics, while others do non-phylogenetic multivariate analysis. It can also be used to build timetrees incorporating a geological timescale, with some optional modules. | Maximum parsimony, distance matrix, maximum likelihood | Wayne Maddison and D. R. Maddison |
MetaPIGA2 | Maximum likelihood phylogeny inference multi-core program for DNA and protein sequences, and morphological data. Analyses can be performed using an extensive and user-friendly graphical interface or by using batch files. It also implements tree visualization tools, ancestral sequences, and automated selection of best substitution model and parameters. | Maximum likelihood, stochastic heuristics (genetic algorithm, metapopulation genetic algorithm, simulated annealing, etc.), discrete Gamma rate heterogeneity, ancestral state reconstruction, model testing | Michel C. Milinkovitch and Raphaël Helaers |
MicrobeTrace | MicrobeTrace is a free, browser-based web application. | 2D and 3D network visualization tool, Neighbor-joining tree visualization, Gantt charts, bubbles charts, networks visualized on maps, flow diagrams, aggregate tables, epi curves, histograms, alignment viewer, and much more. | Ellsworth M. Campbell, Anthony Boyles, Anupama Shankar, Jay Kim, Sergey Knyazev, Roxana Cintron, William M. Switzer [24] |
MNHN-Tree-Tools | MNHN-Tree-Tools is an opensource phylogenetics inference software working on nucleic and protein sequences. | Clustering of DNA or protein sequences and phylogenetic tree inference from a set of sequences. At the core it employs a distance-density based approach. | Thomas Haschka, Loïc Ponger, Christophe Escudé and Julien Mozziconacci [25] |
Modelgenerator | Model selection (protein or nucleotide) | Maximum likelihood | Thomas Keane |
MOLPHY | Molecular phylogenetics (protein or nucleotide) | Maximum likelihood | J. Adachi and M. Hasegawa |
MorphoBank | Web application to organize trait data (morphological characters) for tree building | for use with Maximum Parsimony (via the CIPRES portal), Maximum Likelihood, and Bayesian analysis) | O'Leary, M. A., and S. Kaufman, [26] also K. Alphonse |
MrBayes | Posterior probability estimation | Bayesian inference | J. Huelsenbeck, et al. [27] |
Network | Free Phylogenetic Network Software | Median Joining, Reduced Median, Steiner Network | A. Roehl |
Nona | Phylogenetic inference | Maximum parsimony, implied weighting, ratchet | P. Goloboff |
PAML | Phylogenetic analysis by maximum likelihood | Maximum likelihood and Bayesian inference | Z. Yang |
ParaPhylo [28] | Computation of gene and species trees based on event-relations (orthology, paralogy) | Cograph-Editing and Triple-Inference | Hellmuth |
PartitionFinder | Combined selection of models of molecular evolution and partitioning schemes for DNA and protein alignments | Maximum likelihood, AIC, AICc, BIC | R. Lanfear, B Calcott, SYW Ho, S Guindon |
PASTIS | R package for phylogenetic assembly | R, two‐stage Bayesian inference using MrBayes 3.2 | Thomas et al. 2013 [29] |
PAUP* | Phylogenetic analysis using parsimony (*and other methods) | Maximum parsimony, distance matrix, maximum likelihood | D. Swofford |
phangorn [30] | Phylogenetic analysis in R | ML, MP, distance matrix, bootstrap, phylogentic networks, bootstrap, model selection, SH-test, SOWH-test | Maintainer: K. Schliep |
Phybase [31] | an R package for species tree analysis | phylogenetics functions, STAR, NJst, STEAC, maxtree, etc | L. Liu & L. Yu |
phyclust | Phylogenetic Clustering (Phyloclustering) | Maximum likelihood of Finite Mixture Modes | Wei-Chen Chen |
PHYLIP | PHYLogeny Inference Package | Maximum parsimony, distance matrix, maximum likelihood | J. Felsenstein |
phyloT | Generates phylogenetic trees in various formats, based on NCBI taxonomy | none | I. Letunic |
PhyloQuart | Quartet implementation (uses sequences or distances) | Quartet method | V. Berry |
PhyloWGS | Reconstructing subclonal composition and evolution from whole-genome sequencing of tumors | MCMC | A. G. Deshwar, S. Vembu, C. K. Yung, G. H. Jang, L. Stein, and Q. Morris |
PhyML [32] | Fast and accurate estimation of phylogenies using maximum likelihood | Maximum likelihood | S. Guindon & O. Gascuel |
phyx [33] | Unix/Linux command line phylogenetic tools | Explore, manipulate, analyze, and simulate phylogenetic objects (alignments, trees, and MCMC logs) | J.W. Brown, J.F. Walker, and S.A. Smith |
POY | A phylogenetic analysis program that supports multiple kinds of data and can perform alignment and phylogeny inference. A variety of heuristic algorithms have been developed for this purpose | Maximum parsimony, Maximum likelihood, Chromosome rearrangement, discreet characters, continuous characters, Alignment | A. Varon, N. Lucaroni, L. Hong, W. Wheeler |
ProtASR2 [34] | Ancestral reconstruction of protein sequences accounting for folding stability | Maximum likelihood, substitution models | M. Arenas, U. Bastolla |
ProtEvol | Simulation of protein sequences under structurally constrained substitution models | Simulating sequences, substitution models | M. Arenas, A. Sanchez-Cobos, U. Bastolla U |
ProteinEvolver | Simulation of protein sequences along phylogenies under empirical and structurally constrained substitution models of protein evolution | Simulating sequences forward in time, substitution models | M. Arenas, H.G. Dos Santos, D. Posada, U. Bastolla |
ProteinEvolverABC [35] | Coestimation of recombination and substitution rates in protein sequences | Approximate Bayesian computation | M. Arenas |
ProteinModelerABC [36] | Selection among site-dependent structurally constrained substitution models of protein evolution | Approximate Bayesian computation | D. Ferreiro et al |
ProtTest3 | A high-performance computing program for selecting the model of protein evolution that best fits a given set of aligned sequences | Maximum likelihood, AIC, BIC, DT | D. Darriba, GL. Taboada, R. Doallo, D. Posada |
PyCogent | Software library for genomic biology | Simulating sequences, alignment, controlling third party applications, workflows, querying databases, generating graphics and phylogenetic trees | Knight et al. |
QuickTree | Tree construction optimized for efficiency | Neighbor-joining | K. Howe, A. Bateman, R. Durbin |
RAxML-HPC | Randomized Axelerated Maximum Likelihood for High Performance Computing (nucleotides and aminoacids) | Maximum likelihood, simple Maximum parsimony | A. Stamatakis |
RAxML-NG [37] | Randomized Axelerated Maximum Likelihood for High Performance Computing (nucleotides and aminoacids) Next Generation | Maximum likelihood, simple Maximum parsimony | A. Kozlov, D. Darriba, T. Flouri, B. Morel, A. Stamatakis |
SEMPHY | Tree reconstruction using the combined strengths of maximum-likelihood (accuracy) and neighbor-joining (speed). SEMPHY has become outdated. The authors now refer users to RAxML, which is superior in accuracy and speed. | A hybrid maximum-likelihood – neighbor-joining method | M. Ninio, E. Privman, T. Pupko, N. Friedman |
SGWE | Simulation of genome-wide evolution along phylogenetic trees | Simulating genome-wide sequences forward time | Arenas M., Posada D. |
SimPlot++ [38] | Sequence similarity plots (SimPlots [39] ), detection of intragenic and intergenic recombination events, bootscan analysis [40] and sequence similarity networks | SimPlot using different nucleotide/protein distance models; Phi, χ2 and NSS recombination tests; Sequence similarity network analysis | S. Samson, E. Lord, V. Makarenkov |
sowhat [41] | Hypothesis testing | SOWH test | Church, Ryan, Dunn |
Splatche3 [42] | Simulation of genetic data under diverse spatially explicit evolutionary scenarios | Coalescent, molecular evolution, DNA sequences, SNPs, STRs, RFLPs | M. Currat et al. |
SplitsTree [43] | Tree and network program | Computation, visualization and exploration of phylogenetic trees and networks | D.H. Huson and D. Bryant |
TNT | Phylogenetic inference | Parsimony, weighting, ratchet, tree drift, tree fusing, sectorial searches | P. Goloboff et al. |
TOPALi | Phylogenetic inference | Phylogenetic model selection, Bayesian analysis and Maximum Likelihood phylogenetic tree estimation, detection of sites under positive selection, and recombination breakpoint location analysis | Iain Milne, Dominik Lindner et al. |
TreeGen | Tree construction given precomputed distance data | Distance matrix | ETH Zurich |
TreeAlign | Efficient hybrid method | Distance matrix and approximate parsimony | J. Hein |
TreeLine | Tree construction algorithm within the DECIPHER package for R | Maximum likelihood, maximum parsimony, and distance | E. Wright |
Treefinder [44] | Fast ML tree reconstruction, bootstrap analysis, model selection, hypothesis testing, tree calibration, tree manipulation and visualization, computation of sitewise rates, sequence simulation, many models of evolution (DNA, protein, rRNA, mixed protein, user-definable), GUI and scripting language | Maximum likelihood, distances, and others | Jobb G, von Haeseler A, Strimmer K |
Tree-Puzzle [45] [46] | Maximum likelihood and statistical analysis | Maximum likelihood | Makarenkov |
T-REX (Webserver) [47] | Tree inference and visualization, Horizontal gene transfer detection, multiple sequence alignment | Distance (neighbor joining), Parsimony and Maximum likelihood (PhyML, RAxML) tree inference, MUSCLE, MAFFT and ClustalW sequence alignments and related applications | Boc A, Diallo AB, Makarenkov V |
UShER [48] | Phylogenetic placement using maximum parsimony for viral genomes | Maximum parsimony | Turakhia Y, Thornlow B, Hinrichs AS, De Maio N, Gozashti L, Lanfear R, Haussler D and Corbett-Detig R |
UGENE | Fast and free multiplatform tree editor | GUI with PHYLIP 3.6 and IQTree algorithms | Unipro |
VeryFastTree [49] | A highly-tuned tool that uses parallelizing and vectorizing strategies to speed inference of phylogenies for huge alignments | Approximate maximum likelihood | César Piñeiro. José M. Abuín and Juan C. Pichel |
Winclada | GUI and tree editor (requires Nona) | Maximum parsimony, ratchet | K. Nixon |
Xrate | Phylo-grammar engine | Rate estimation, branch length estimation, alignment annotation | I. Holmes |
In biology, phylogenetics is the study of the evolutionary history of life using genetics, which is known as phylogenetic inference. It establishes the relationship between organisms with the empirical data and observed heritable traits of DNA sequences, protein amino acid sequences, and morphology. The results are a phylogenetic tree—a diagram setting the hypothetical relationships between organisms and their evolutionary history.
A phylogenetic tree, phylogeny or evolutionary tree is a graphical representation which shows the evolutionary history between a set of species or taxa during a specific time. In other words, it is a branching diagram or a tree showing the evolutionary relationships among various biological species or other entities based upon similarities and differences in their physical or genetic characteristics. In evolutionary biology, all life on Earth is theoretically part of a single phylogenetic tree, indicating common ancestry. Phylogenetics is the study of phylogenetic trees. The main challenge is to find a phylogenetic tree representing optimal evolutionary ancestry between a set of species or taxa. Computational phylogenetics focuses on the algorithms involved in finding optimal phylogenetic tree in the phylogenetic landscape.
The molecular clock is a figurative term for a technique that uses the mutation rate of biomolecules to deduce the time in prehistory when two or more life forms diverged. The biomolecular data used for such calculations are usually nucleotide sequences for DNA, RNA, or amino acid sequences for proteins.
In biology, a substitution model, also called models of sequence evolution, are Markov models that describe changes over evolutionary time. These models describe evolutionary changes in macromolecules, such as DNA sequences or protein sequences, that can be represented as sequence of symbols. Substitution models are used to calculate the likelihood of phylogenetic trees using multiple sequence alignment data. Thus, substitution models are central to maximum likelihood estimation of phylogeny as well as Bayesian inference in phylogeny. Estimates of evolutionary distances are typically calculated using substitution models. Substitution models are also central to phylogenetic invariants because they are necessary to predict site pattern frequencies given a tree topology. Substitution models are also necessary to simulate sequence data for a group of organisms related by a specific tree.
Phylogenomics is the intersection of the fields of evolution and genomics. The term has been used in multiple ways to refer to analysis that involves genome data and evolutionary reconstructions. It is a group of techniques within the larger fields of phylogenetics and genomics. Phylogenomics draws information by comparing entire genomes, or at least large portions of genomes. Phylogenetics compares and analyzes the sequences of single genes, or a small number of genes, as well as many other types of data. Four major areas fall under phylogenomics:
A phylogenetic network is any graph used to visualize evolutionary relationships between nucleotide sequences, genes, chromosomes, genomes, or species. They are employed when reticulation events such as hybridization, horizontal gene transfer, recombination, or gene duplication and loss are believed to be involved. They differ from phylogenetic trees by the explicit modeling of richly linked networks, by means of the addition of hybrid nodes instead of only tree nodes. Phylogenetic trees are a subset of phylogenetic networks. Phylogenetic networks can be inferred and visualised with software such as SplitsTree, the R-package, phangorn, and, more recently, Dendroscope. A standard format for representing phylogenetic networks is a variant of Newick format which is extended to support networks as well as trees.
Computational phylogenetics, phylogeny inference, or phylogenetic inference focuses on computational and optimization algorithms, heuristics, and approaches involved in phylogenetic analyses. The goal is to find a phylogenetic tree representing optimal evolutionary ancestry between a set of genes, species, or taxa. Maximum likelihood, parsimony, Bayesian, and minimum evolution are typical optimality criteria used to assess how well a phylogenetic tree topology describes the sequence data. Nearest Neighbour Interchange (NNI), Subtree Prune and Regraft (SPR), and Tree Bisection and Reconnection (TBR), known as tree rearrangements, are deterministic algorithms to search for optimal or the best phylogenetic tree. The space and the landscape of searching for the optimal phylogenetic tree is known as phylogeny search space.
PHYLogeny Inference Package (PHYLIP) is a free computational phylogenetics package of programs for inferring evolutionary trees (phylogenies). It consists of 65 portable programs, i.e., the source code is written in the programming language C. As of version 3.696, it is licensed as open-source software; versions 3.695 and older were proprietary software freeware. Releases occur as source code, and as precompiled executables for many operating systems including Windows, Mac OS 8, Mac OS 9, OS X, Linux ; and FreeBSD from FreeBSD.org. Full documentation is written for all the programs in the package and is included therein. The programs in the phylip package were written by Professor Joseph Felsenstein, of the Department of Genome Sciences and the Department of Biology, University of Washington, Seattle.
Ancestral reconstruction is the extrapolation back in time from measured characteristics of individuals, populations, or species to their common ancestors. It is an important application of phylogenetics, the reconstruction and study of the evolutionary relationships among individuals, populations or species to their ancestors. In the context of evolutionary biology, ancestral reconstruction can be used to recover different kinds of ancestral character states of organisms that lived millions of years ago. These states include the genetic sequence, the amino acid sequence of a protein, the composition of a genome, a measurable characteristic of an organism (phenotype), and the geographic range of an ancestral population or species. This is desirable because it allows us to examine parts of phylogenetic trees corresponding to the distant past, clarifying the evolutionary history of the species in the tree. Since modern genetic sequences are essentially a variation of ancient ones, access to ancient sequences may identify other variations and organisms which could have arisen from those sequences. In addition to genetic sequences, one might attempt to track the changing of one character trait to another, such as fins turning to legs.
Bayesian inference of phylogeny combines the information in the prior and in the data likelihood to create the so-called posterior probability of trees, which is the probability that the tree is correct given the data, the prior and the likelihood model. Bayesian inference was introduced into molecular phylogenetics in the 1990s by three independent groups: Bruce Rannala and Ziheng Yang in Berkeley, Bob Mau in Madison, and Shuying Li in University of Iowa, the last two being PhD students at the time. The approach has become very popular since the release of the MrBayes software in 2001, and is now one of the most popular methods in molecular phylogenetics.
TREE-PUZZLE is a computer program used to construct phylogenetic trees from sequence data by maximum likelihood analysis. Branch lengths can be calculated with and without the molecular clock hypothesis.
A supertree is a single phylogenetic tree assembled from a combination of smaller phylogenetic trees, which may have been assembled using different datasets or a different selection of taxa. Supertree algorithms can highlight areas where additional data would most usefully resolve any ambiguities. The input trees of a supertree should behave as samples from the larger tree.
Ziheng Yang FRS is a Chinese biologist. He holds the R.A. Fisher Chair of Statistical Genetics at University College London, and is the Director of R.A. Fisher Centre for Computational Biology at UCL. He was elected a Fellow of the Royal Society in 2006.
T-REX is a freely available web server, developed at the department of Computer Science of the Université du Québec à Montréal, dedicated to the inference, validation and visualization of phylogenetic trees and phylogenetic networks. The T-REX web server allows the users to perform several popular methods of phylogenetic analysis as well as some new phylogenetic applications for inferring, drawing and validating phylogenetic trees and networks.
Bacterial phylodynamics is the study of immunology, epidemiology, and phylogenetics of bacterial pathogens to better understand the evolutionary role of these pathogens. Phylodynamic analysis includes analyzing genetic diversity, natural selection, and population dynamics of infectious disease pathogen phylogenies during pandemics and studying intra-host evolution of viruses. Phylodynamics combines the study of phylogenetic analysis, ecological, and evolutionary processes to better understand of the mechanisms that drive spatiotemporal incidence and phylogenetic patterns of bacterial pathogens. Bacterial phylodynamics uses genome-wide single-nucleotide polymorphisms (SNP) in order to better understand the evolutionary mechanism of bacterial pathogens. Many phylodynamic studies have been performed on viruses, specifically RNA viruses which have high mutation rates. The field of bacterial phylodynamics has increased substantially due to the advancement of next-generation sequencing and the amount of data available.
Multispecies Coalescent Process is a stochastic process model that describes the genealogical relationships for a sample of DNA sequences taken from several species. It represents the application of coalescent theory to the case of multiple species. The multispecies coalescent results in cases where the relationships among species for an individual gene can differ from the broader history of the species. It has important implications for the theory and practice of phylogenetics and for understanding genome evolution.
Arndt von Haeseler is a German bioinformatician and evolutionary biologist. He is the scientific director of the Max F. Perutz Laboratories at the Vienna Biocenter and a professor of bioinformatics at the University of Vienna and the Medical University of Vienna.
Minimum evolution is a distance method employed in phylogenetics modeling. It shares with maximum parsimony the aspect of searching for the phylogeny that has the shortest total sum of branch lengths.
In phylogenetics, reconciliation is an approach to connect the history of two or more coevolving biological entities. The general idea of reconciliation is that a phylogenetic tree representing the evolution of an entity can be drawn within another phylogenetic tree representing an encompassing entity to reveal their interdependence and the evolutionary events that have marked their shared history. The development of reconciliation approaches started in the 1980s, mainly to depict the coevolution of a gene and a genome, and of a host and a symbiont, which can be mutualist, commensalist or parasitic. It has also been used for example to detect horizontal gene transfer, or understand the dynamics of genome evolution.