View source for Inferring Phylogenies

'''''Inferring Phylogenies''''' (ISBN ) by Joseph Felsenstein.

== Table of Contents ==
* PREFACE
* '''1. Parsimony methods'''
** A simple example
*** Evaluating a particular tree
*** Rootedness and unrootedness
** Methods of rooting the tree
** Branch lengths
** Unresolved questions
* '''2. Counting evolutionary changes'''
 <ul>
 <li>The Fitch algorithm</li>
 <li>The Sankoff algorithm</li>
 <ul>
 <li>Connection between the two algorithms</li>
 </ul>
 <li>Using the algorithms when modifying trees</li>
 <ul>
 <li>Views</li>
 <li>Using views when a tree is altered</li>
 </ul>
 <li>Further economies</li>
 </ul>
* '''3. How many trees are there?'''
 <ul>
 <li>Rooted bifurcating trees</li>
 <li>Unrooted bifurcating trees</li>
 <li>Multifurcating trees</li>
 <ul>
 <li>Unrooted trees with multifurcations</li>
 </ul>
 <li>Tree shapes</li>
 <ul>
 <li>Rooted bifurcating tree shapes</li>
 <li>Rooted multifurcating tree shapes</li>
 <li>Unrooted Shapes</li>
 </ul>
 <li>Labeled histories</li>
 <li>Perspective</li>
 </ul>
* '''4. Finding the best tree by heuristic search'''
 <ul>
 <li>Nearest-neighbor interchanges</li>
 <li>Subtree pruning and regrafting</li>
 <li>Tree bisection and reconnection</li>
 <li>Other tree rearrangement methods</li>
 <ul>
 <li>Tree-fusing</li>
 <li>Genetic algorithms</li>
 <li>Tree windows and sectorial search</li>
 </ul>
 <li>Speeding up rearrangements</li>
 <li>Sequential addition</li>
 <li>Star decomposition</li>
 <li>Tree space</li>
 <li>Search by reweighting of characters</li>
 <li>Simulated annealing</li>
 <li>History</li>
 </ul>
* '''5. Finding the best tree by branch and bound'''
 <ul>
 <li>A nonbiological example</li>
 <li>Finding the optimal solution</li>
 <li>NP-hardness</li>
 <li>Branch and bound methods</li>
 <li>Phylogenies: Despair and hope</li>
 <li>Branch and bound for parsimony</li>
 <li>Improving the bound</li>
 <ul>
 <li>Using still-absent states</li>
 <li>Using compatibility</li>
 </ul>
 <li>Rules limiting the search</li>
 </ul>
* '''6. Ancestral states and branch lengths'''
 <ul>
 <li>Reconstructing ancestral states</li>
 <li>Accelerated and delayed transformation</li>
 <li>Branch lengths</li>
 </ul>
* '''7. Variants of parsimony'''
 <ul>
 <li>Camin-Sokal parsimony</li>
 <li>Parsimony on an ordinal scale</li>
 <li>Dollo parsimony</li>
 <li>Polymorphism parsimony</li>
 <li>Unknown ancestral states</li>
 <li>Multiple states and binary coding</li>
 <li>Dollo parsimony and multiple states</li>
 <li>Polymorphism parsimony and multiple states</li>
 <li>Transformation series analysis</li>
 <li>Weighting characters</li>
 <li>Successive weighting and nonlinear weighting</li>
 <ul>
 <li>Successive weighting</li>
 <li>Nonsuccessive algorithms</li>
 </ul>
 </ul>
* '''8. Compatibility'''
 <ul>
 <li>Testing compatibility</li>
 <li>The Pairwise Compatibility Theorem</li>
 <li>Cliques of compatible characters</li>
 <li>Finding the tree from the clique</li>
 <li>Other cases where cliques can be used</li>
 <li>Where cliques cannot be used</li>
 <ul>
 <li>Perfect phylogeny</li>
 <li>Using compatibility on molecules anyway</li>
 </ul>
 </ul>
* '''9. Statistical properties of parsimony'''
 <ul>
 <li>Likelihood and parsimony</li>
 <ul>
 <li>The weights</li>
 <li>Unweighted parsimony</li>
 <li>Limitations of this justification of parsimony</li>
 <li>Farris&#8217;s proofs</li>
 <li>No common mechanism</li>
 <li>Likelihood and compatibility</li>
 <li>Parsimony versus compatibility</li>
 </ul>
 <li>Consistency and parsimony</li>
 <ul>
 <li>Character patterns and parsimony</li>
 <li>Observed numbers of the patterns</li>
 <li>Observed fractions of the patterns</li>
 <li>Expected fractions of the patterns</li>
 <li>Inconsistency</li>
 <li>When inconsistency is not a problem</li>
 <li>The nucleotide sequence case</li>
 <li>Other situations where consistency is guaranteed</li>
 <li>Does a molecular clock guarantee consistency?</li>
 <li>The Farris zone</li>
 </ul>
 <li>Some perspective</li>
 </ul>
* '''10. A digression on history and philosophy'''
 <ul>
 <li>How phylogeny algorithms developed</li>
 <ul>
 <li>Sokal and Sneath</li>
 <li>Edwards and Cavalli-Sforza</li>
 <li>Camin and Sokal and parsimony</li>
 <li>Eck and Dayhoff and molecular parsimony</li>
 <li>Fitch and Margoliash popularize distance matrix methods</li>
 <li>Wilson and Le Quesne introduce compatibility</li>
 <li>Jukes and Cantor and molecular distances</li>
 <li>Farris and Kluge and unordered parsimony</li>
 <li>Fitch and molecular parsimony</li>
 <li>Further work</li>
 <li>What about Willi Hennig and Walter Zimmerman?</li>
 </ul>
 <li>Different philosophical frameworks</li>
 <ul>
 <li>Hypothetico-deductive</li>
 <li>Logical parsimony</li>
 <li>Logical probability?</li>
 <li>Criticisms of statistical inference</li>
 <li>The irrelevance of classification</li>
 </ul>
 </ul>
* '''11. Distance matrix methods'''
 <ul>
 <li>Branch lengths and times</li>
 <li>The least squares methods</li>
 <ul>
 <li>Least squares branch lengths</li>
 <li>Finding the least squares tree topology</li>
 </ul>
 <li>The statistical rationale</li>
 <li>Generalized least squares</li>
 <li>Distances</li>
 <li>The [[Jukes-Cantor model]]&#8212;-an example</li>
 <li>Why correct for multiple changes?</li>
 <li>Minimum evolution</li>
 <li>Clustering algorithms</li>
 <li>UPGMA and least squares</li>
 <ul>
 <li>A clustering algorithm</li>
 <li>An example</li>
 <li>UPGMA on nonclocklike trees</li>
 </ul>
 <li>Neighbor-joining</li>
 <ul>
 <li>Performance</li>
 <li>Using neighbor-joining with other methods</li>
 <li>Relation of neighbor-joining to least squares</li>
 <li>Weighted versions of neighbor-joining</li>
 </ul>
 <li>Other approximate distance methods</li>
 <ul>
 <li>Distance Wagner method</li>
 <li>A related family</li>
 <li>Minimizing the maximum discrepancy</li>
 <li>Two approaches to error in trees</li>
 </ul>
 <li>A puzzling formula</li>
 <li>Consistency and distance methods</li>
 <li>A limitation of distance methods</li>
 </ul>
* '''12. Quartets of species'''
 <ul>
 <li>The four point metric</li>
 <li>The split decomposition</li>
 <ul>
 <li>Related methods</li>
 </ul>
 <li>Short quartets methods</li>
 <li>The disk-covering method</li>
 <li>Challenges for the short quartets and DCM methods</li>
 <li>Three-taxon statement methods</li>
 <li>Other uses of quartets with parsimony</li>
 <li>Consensus supertrees</li>
 <li>Neighborliness</li>
 <li>De Soete&#8217;s search method</li>
 <li>Quartet puzzling and searching tree space</li>
 <li>Perspective</li>
 </ul>
* '''13. Models of DNA evolution'''
 <ul>
 <li>Kimura&#8217;s two-parameter model</li>
 <li>Calculation of the distance</li>
 <li>The Tamura-Nei model, F84, and HKY</li>
 <li>The general time-reversible model</li>
 <ul>
 <li>Distances from the GTR model</li>
 </ul>
 <li>The general 12-parameter model</li>
 <li>LogDet distances</li>
 <li>Other distances</li>
 <li>Variance of distance</li>
 <li>Rate variation between sites or loci</li>
 <ul>
 <li>Different rates at different sites</li>
 <li>Distances with known rates</li>
 <li>Distribution of rates</li>
 <li>Gamma- and lognormally distributed rates</li>
 </ul>
 <ul>
 <li>Distances from gamma-distributed rates</li>
 </ul>
 <li>Models with nonindependence of sites</li>
 </ul>
* '''14. Models of protein evolution'''
 <ul>
 <li>Amino acid models</li>
 <li>The Dayhoff model</li>
 <li>Other empirically-based models</li>
 <ul>
 <li>Models depending on secondary structure</li>
 </ul>
 <li>Codon-based models</li>
 <ul>
 <li>Inequality of synonymous and nonsynonymous substitutions</li>
 </ul>
 <li>Protein structure and correlated change</li>
 </ul>
* '''15. Restriction sites, RAPDs, AFLPs, and microsatellites'''
 <ul>
 <li>Restriction sites</li>
 <ul>
 <li>Nei and Tajima&#8217;s model</li>
 <li>Distances based on restriction sites</li>
 <li>Issues of ascertainment</li>
 <li>Parsimony for restriction sites</li>
 </ul>
 <li>Modeling restriction fragments</li>
 <ul>
 <li>Parsimony with restriction fragments</li>
 </ul>
 <li>RAPDs and AFLPs</li>
 <ul>
 <li>The issue of dominance</li>
 <li>Unresolved problems</li>
 <li>Microsatellite models</li>
 <li>The one-step model</li>
 <li>Microsatellite distances</li>
 <li>A Brownian motion approximation</li>
 <li>Models with constraints on array size</li>
 <li>Multi-step and heterogeneous models</li>
 <li>Snakes and Ladders</li>
 <li>Complications</li>
 </ul>
 </ul>
* '''16. Likelihood methods'''
 <ul>
 <li>Maximum likelihood</li>
 <ul>
 <li>An example</li>
 </ul>
 <li>Computing the likelihood of a tree</li>
 <ul>
 <li>Economizing on the computation</li>
 <li>Handling ambiguity and error</li>
 </ul>
 <li>Unrootedness</li>
 <li>Finding the maximum likelihood tree</li>
 <li>Inferring ancestral sequences</li>
 <li>Rates varying among sites</li>
 <ul>
 <li>Hidden Markov models</li>
 <li>Autocorrelation of rates</li>
 <li>HMMs for other aspects of models</li>
 <li>Estimating the states</li>
 </ul>
 <li>Models with clocks</li>
 <ul>
 <li>Relaxing molecular clocks</li>
 <li>Models for relaxed clocks</li>
 <li>Covarions</li>
 <li>Empirical approaches to change of rates</li>
 </ul>
 <li>Are ML estimates consistent?</li>
 <ul>
 <li>Comparability of likelihoods</li>
 <li>A nonexistent proof?</li>
 <li>A simple proof</li>
 <li>Misbehavior with the wrong model</li>
 <li>Better behavior with the wrong model</li>
 </ul>
 </ul>
* '''17. Hadamard methods'''
 <ul>
 <li>The edge length spectrum and conjugate spectrum</li>
 <li>The closest tree criterion</li>
 <li>DNA models</li>
 <li>Computational effort</li>
 <li>Extensions of Hadamard methods</li>
 </ul>
* '''18. Bayesian inference of phylogenies'''
 <ul>
 <li>Bayes&#8217; theorem</li>
 <li>Bayesian methods for phylogenies</li>
 <li>Markov chain Monte Carlo methods</li>
 <li>The Metropolis algorithm</li>
 <ul>
 <li>Its equilibrium distribution</li>
 <li>Bayesian MCMC</li>
 </ul>
 <li>Bayesian MCMC for phylogenies</li>
 <ul>
 <li>Priors</li>
 </ul>
 <li>Proposal distributions</li>
 <li>Computing the likelihoods</li>
 <li>Summarizing the posterior</li>
 <li>Priors on trees</li>
 <li>Controversies over Bayesian inference</li>
 <ul>
 <li>Universality of the prior</li>
 <li>Flat priors and doubts about them</li>
 </ul>
 <li>Applications of Bayesian methods</li>
 </ul>
* '''19. Testing models, trees, and clocks'''
 <ul>
 <li>Likelihood and tests</li>
 <li>Likelihood ratios near asymptopia</li>
 <li>Multiple parameters</li>
 <ul>
 <li>Some parameters constrained, some not</li>
 <li>Conditions</li>
 <li>Curvature or height?</li>
 </ul>
 <li>Interval estimates</li>
 <li>Testing assertions about parameters</li>
 <ul>
 <li>Coins in a barrel</li>
 <li>Evolutionary rates instead of coins</li>
 </ul>
 <li>Choosing among nonnested hypotheses: AIC and BIC</li>
 <ul>
 <li>An example using the AIC criterion</li>
 </ul>
 <li>The problem of multiple topologies</li>
 <ul>
 <li>LRTs and single branches</li>
 </ul>
 <li>Interior branch tests</li>
 <ul>
 <li>Interior branch tests using parsimony</li>
 <li>A multiple-branch counterpart of interior branch tests</li>
 </ul>
 <li>Testing the molecular clock</li>
 <ul>
 <li>Parsimony-based methods</li>
 <li>Distance-based methods</li>
 <li>Likelihood-based methods</li>
 <li>The relative rate test</li>
 </ul>
 <li>Simulation tests based on likelihood</li>
 <ul>
 <li>Further literature</li>
 </ul>
 <li>More exact tests and confidence intervals</li>
 <ul>
 <li>Tests for three species with a clock</li>
 <li>Bremer support</li>
 <li>Zander&#8217;s conditional probability of reconstruction</li>
 <li>More generalized confidence sets</li>
 </ul>
 </ul>
* '''20. Bootstrap, jackknife, and permutation tests'''
 <ul>
 <li>The bootstrap and the jackknife</li>
 <li>Bootstrapping and phylogenies</li>
 <li>The delete-half jackknife</li>
 <li>The bootstrap and jackknife for phylogenies</li>
 <li>The multiple-tests problem</li>
 <li>Independence of characters</li>
 <li>Identical distribution &#8212;- a problem?</li>
 <li>Invariant characters and resampling methods</li>
 <li>Biases in bootstrap and jackknife probabilities</li>
 <ul>
 <li>$P$ values in a simple normal case</li>
 <li>Methods of reducing the bias</li>
 <li>The drug testing analogy</li>
 </ul>
 <li>Alternatives to <em>P</em> values</li>
 <ul>
 <li>Probabilities of trees</li>
 <li>Using tree distances</li>
 <li>Jackknifing species</li>
 </ul>
 <li>Parametric bootstrapping</li>
 <ul>
 <li>Advantages and disadvantages of the parametric bootstrap</li>
 </ul>
 <li>Permutation tests</li>
 <ul>
 <li>Permuting species within characters</li>
 </ul>
 <ul>
 <li>Permuting characters</li>
 <li>Skewness of tree length distribution</li>
 </ul>
 </ul>
* '''21. Paired-sites tests'''
 <ul>
 <li>An example</li>
 <li>Multiple trees</li>
 <ul>
 <li>The SH test</li>
 <li>Other multiple-comparison tests</li>
 </ul>
 <li>Testing other parameters</li>
 <li>Perspective</li>
 </ul>
* '''22. Invariants'''
 <ul>
 <li>Symmetry invariants</li>
 <li>Three-species invariants</li>
 <li>Lake&#8217;s linear invariants</li>
 <li>Cavender&#8217;s quadratic invariants</li>
 <ul>
 <li>The <em>K</em> invariants</li>
 <li>The <em>L</em> invariants</li>
 <li>Generalization of Cavender&#8217;s <em>L</em> invariants</li>
 </ul>
 <li>Drolet and Sankoff&#8217;s <em>k</em>-state quadratic invariants</li>
 <li>Clock invariants</li>
 <li>General methods for finding invariants</li>
 <ul>
 <li>Fourier transform methods</li>
 <li>Gröbner bases and other general methods</li>
 <li>Expressions for all the 3ST invariants</li>
 <li>Finding all invariants empirically</li>
 <li>All linear invariants</li>
 <li>Special cases and extensions</li>
 </ul>
 <li>Invariants and evolutionary rates</li>
 <li>Testing invariants</li>
 <li>What use are invariants?</li>
 </ul>
* '''23. Brownian motion and gene frequencies'''
 <ul>
 <li>Brownian motion</li>
 <li>Likelihood for a phylogeny</li>
 <li>What likelihood to compute?</li>
 <ul>
 <li>Assuming a clock</li>
 <li>The REML approach</li>
 </ul>
 <li>Multiple characters and Kronecker products</li>
 <li>Pruning the likelihood</li>
 <li>Maximizing the likelihood</li>
 <li>Inferring ancestral states</li>
 <ul>
 <li>Squared-change parsimony</li>
 </ul>
 <li>Gene frequencies and Brownian motion</li>
 <ul>
 <li>Using approximate Brownian motion</li>
 <li>Distances from gene frequencies</li>
 <li>A more exact likelihood method</li>
 <li>Gene frequency parsimony</li>
 </ul>
 </ul>
* '''24. Quantitative characters'''
 <ul>
 <li>Neutral models of quantitative characters</li>
 <li>Changes due to natural selection</li>
 <ul>
 <li>Selective correlation</li>
 <li>Covariances of multiple characters in multiple lineages</li>
 <li>Selection for an optimum</li>
 <li>Brownian motion and selection</li>
 </ul>
 <li>Correcting for correlations</li>
 <li>Punctuational models</li>
 <li>Inferring phylogenies and correlations</li>
 <li>Chasing a common optimum</li>
 <li>The character-coding &#8220;problem&#8221;</li>
 <li>Continuous-character parsimony methods</li>
 <ul>
 <li>Manhattan metric parsimony</li>
 <li>Other parsimony methods</li>
 </ul>
 <li>Threshold models</li>
 </ul>
* '''25. Comparative methods'''
 <ul>
 <li>An example with discrete states</li>
 <li>An example with continuous characters</li>
 <li>The contrasts method</li>
 <li>Correlations between characters</li>
 <li>When the tree is not completely known</li>
 <li>Inferring change in a branch</li>
 <li>Sampling error</li>
 <li>The standard regression and other variations</li>
 <ul>
 <li>Generalized least squares</li>
 <li>Phylogenetic autocorrelation</li>
 <li>Transformations of time</li>
 <li>Should we use the phylogeny at all?</li>
 </ul>
 <li>Paired-lineage tests</li>
 <li>Discrete characters</li>
 <ul>
 <li>Ridley&#8217;s method</li>
 <li>Concentrated-changes tests</li>
 <li>A paired-lineages test</li>
 <li>Methods using likelihood</li>
 <li>Advantages of the likelihood approach</li>
 </ul>
 <li>Molecular applications</li>
 </ul>
* '''26. Coalescent trees'''
 <ul>
 <li>Kingman&#8217;s coalescent</li>
 <li>Bugs in a box—an analogy</li>
 <li>Effect of varying population size</li>
 <li>Migration</li>
 <li>Effect of recombination</li>
 <li>Coalescents and natural selection</li>
 <ul>
 <li>Neuhauser and Krone&#8217;s method</li>
 </ul>
 </ul>
* '''27. Likelihood calculations on coalescents'''
 <ul>
 <li>The basic equation</li>
 <li>Using accurate genealogies—a reverie</li>
 <li>Two random sampling methods</li>
 <ul>
 <li>A Metropolis-Hastings method</li>
 <li>Griffiths and Tavaré&#8217;s method</li>
 </ul>
 <li>Bayesian methods</li>
 <li>MCMC for a variety of coalescent models</li>
 <li>Single-tree methods</li>
 <ul>
 <li>Slatkin and Maddison&#8217;s method</li>
 <li>Fu&#8217;s method</li>
 </ul>
 <li>Summary-statistic methods</li>
 <ul>
 <li>Watterson&#8217;s method</li>
 <li>Other summary-statistic methods</li>
 <li>Testing for recombination</li>
 </ul>
 </ul>
* '''28. Coalescents and species trees'''
 <ul>
 <li>Methods of inferring the species phylogeny</li>
 <ul>
 <li>Reconciled tree parsimony approaches</li>
 <li>Likelihood</li>
 </ul>
 </ul>
* '''29. Alignment, gene families, and genomics'''
 <ul>
 <li>Alignment</li>
 <ul>
 <li>Why phylogenies are important</li>
 </ul>
 <li>Parsimony method</li>
 <ul>
 <li>Approximations and progressive alignment</li>
 </ul>
 <li>Probabilistic models</li>
 <ul>
 <li>Bishop and Thompson&#8217;s method</li>
 <li>The minimum message length method</li>
 <li>The TKF model</li>
 <li>Multibase insertions and deletions</li>
 <li>Tree HMMs</li>
 <li>Trees</li>
 <li>Inferring the alignment</li>
 </ul>
 <li>Gene families</li>
 <ul>
 <li>Reconciled trees</li>
 <li>Reconstructing duplications</li>
 <li>Rooting unrooted trees</li>
 <li>A likelihood analysis</li>
 </ul>
 <li>Comparative genomics</li>
 <ul>
 <li>Tandemly repeated genes</li>
 <li>Inversions</li>
 <li>Inversions in trees</li>
 <li>Inversions, transpositions, and translocations</li>
 <li>Breakpoint and neighbor-coding approximations</li>
 <li>Synteny</li>
 <li>Probabilistic models</li>
 </ul>
 <li>Genome signature methods</li>
 </ul>
* '''30. Consensus trees and distances between trees'''
 <ul>
 <li>Consensus trees</li>
 <ul>
 <li>Strict consensus</li>
 <li>Majority-rule consensus</li>
 <li>Adams consensus tree</li>
 <li>A dismaying result</li>
 <li>Consensus using branch lengths</li>
 <li>Other consensus tree methods</li>
 <li>Consensus subtrees</li>
 </ul>
 <li>Distances between trees</li>
 <ul>
 <li>The symmetric difference</li>
 <li>The quartets distance</li>
 <li>The nearest-neighbor interchange distance</li>
 <li>The path-length-difference metric</li>
 <li>Distances using branch lengths</li>
 <li>Are these distances truly distances?</li>
 <li>Consensus trees and distances</li>
 <li>Trees significantly the same? different?</li>
 </ul>
 <li>What do consensus trees and tree distances tell us?</li>
 <ul>
 <li>The total evidence debate</li>
 <li>A modest proposal</li>
 </ul>
 </ul>
* '''31. Biogeography, hosts, and parasites'''
 <ul>
 <li>Component compatibility</li>
 <li>Brooks parsimony</li>
 <li>Event-based parsimony methods</li>
 <ul>
 <li>Relation to tree reconciliation</li>
 </ul>
 <li>Randomization tests</li>
 <li>Statistical inference</li>
 </ul>
* '''32. Phylogenies and paleontology'''
 <ul>
 <li>Stratigraphic indices</li>
 <li>Stratophenetics</li>
 <li>Stratocladistics</li>
 <li>Controversies</li>
 <li>A not-quite-likelihood method</li>
 <li>Stratolikelihood</li>
 <ul>
 <li>Making a full likelihood method</li>
 <li>More realistic fossilization models</li>
 </ul>
 <li>Fossils within species: Sequential sampling</li>
 <li>Between species</li>
 </ul>
* '''33. Tests based on tree shape'''
 <ul>
 <li>Using the topology only</li>
 <ul>
 <li>Imbalance at the root</li>
 </ul>
 <li>Harding&#8217;s probabilities of tree shapes</li>
 <li>Tests from shapes</li>
 <ul>
 <li>Measures of overall asymmetry</li>
 <li>Choosing a powerful test</li>
 </ul>
 <li>Tests using times</li>
 <ul>
 <li>Lineage plots</li>
 <li>Likelihood formulas</li>
 <li>Other likelihood approaches</li>
 <li>Other statistical approaches</li>
 <li>A time transformation</li>
 </ul>
 <li>Characters and key innovations</li>
 <li>Work remaining</li>
 </ul>
* '''34. Drawing trees'''
 <ul>
 <li>Issues in drawing rooted trees</li>
 <ul>
 <li>Placement of interior nodes</li>
 <li>Shapes of lineages</li>
 </ul>
 <li>Unrooted trees</li>
 <ul>
 <li>The equal-angle algorithm</li>
 <li>n-Body algorithms</li>
 <li>The equal-daylight algorithm</li>
 </ul>
 <li>Challenges</li>
 </ul>
* '''35. Phylogeny software'''
 <ul>
 <li>Trees, records, and pointers</li>
 <li>Declaring records</li>
 <li>Traversing the tree</li>
 <li>Unrooted tree data structures</li>
 <li>Tree file formats</li>
 <li>Widely used phylogeny programs and packages</li>
 </ul>
* REFERENCES
* INDEX

[[Category:Academic Courses]]
[[Category:Books]]