
@book{nei1987,
	Address = {New York},
	Annote = {LDR    00774cam  2200241 a 4500
001    1933444
005    19950207072013.3
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035    $9(DLC)   86017599
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010    $a   86017599 
020    $a0231063202 (alk. paper)
040    $aDLC$cDLC$dDLC
050 00 $aQH430$b.N45 1987
082 00 $a574.87/328$219
100 1  $aNei, Masatoshi.
245 10 $aMolecular evolutionary genetics /$cMasatoshi Nei.
260    $aNew York :$bColumbia University Press,$c1987.
300    $ax, 512 p. :$bill. ;$c24 cm.
504    $aBibliography: p. [433]-495.
500    $aIncludes indexes.
650  0 $aEvolutionary genetics.
991    $bc-GenColl$hQH430$i.N45 1987$p00004648833$tCopy 1$wBOOKS
},
	Author = {Nei, M.},
	Call-Number = {QH430},
	Date-Added = {2009-08-24 15:50:20 +1200},
	Date-Modified = {2009-08-24 15:51:03 +1200},
	Dewey-Call-Number = {574.87/328},
	Genre = {Evolutionary genetics},
	Isbn = {0231063202 (alk. paper)},
	Library-Id = {86017599},
	Publisher = {Columbia University Press},
	Title = {Molecular evolutionary genetics},
	Year = {1987}}

@book{Avise2004,
	Address = {Sunderland, Mass.},
	Annote = {LDR    01355cam  22003374a 4500
001    13489488
005    20050505103135.0
008    040210s2004    maua     b    001 0 eng  
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925 0  $aacquire$b2 shelf copies$xpolicy default
955    $aNLM$ajc00 2004-02-17 to jc02$djc02 2004-02-17 to technician$ejc03 2004-02-17 to Dewey$aaa07 2004-02-18$aps09 2004-06-18 1 copy rec'd., to CIP ver.$fpv03 2004-07-13 CIP ver. to BCCD$aja15 2004-11-30 Copy 2 to BCCD$ajp14 2005-05-05 c.3 to Discard
010    $a  2004003130
020    $a0878930418 (pbk.)
035    $a(DNLM)101206252
040    $aDNLM/DLC$cDLC$dDLC
042    $apcc
050 00 $aQH438.4.B55$bA95 2004
060 10 $aQH 438.4.B55$bA958m 2004
082 00 $a572.8/6$222
100 1  $aAvise, John C.
245 10 $aMolecular markers, natural history, and evolution /$cJohn C. Avise.
250    $a2nd ed.
260    $aSunderland, Mass. :$bSinauer Associates,$cc2004.
300    $a684 p. :$bill. ;$c24 cm.
504    $aIncludes bibliographical references (p. [543]-661) and indexes.
650  0 $aBiochemical markers.
650  0 $aMolecular evolution.
650 12 $aGenetic Markers.
650 22 $aEvolution, Molecular.
856 41 $3Table of contents$uhttp://www.loc.gov/catdir/toc/ecip0415/2004003130.html
985    $aNLMCIP$d2004-02-13
},
	Author = {Avise, John C},
	Call-Number = {QH438.4.B55},
	Date-Added = {2009-08-24 15:44:39 +1200},
	Date-Modified = {2009-08-24 15:45:00 +1200},
	Dewey-Call-Number = {572.8/6},
	Edition = {2nd ed},
	Genre = {Biochemical markers},
	Isbn = {0878930418 (pbk.)},
	Library-Id = {2004003130},
	Publisher = {Sinauer Associates},
	Title = {Molecular markers, natural history, and evolution},
	Url = {http://www.loc.gov/catdir/toc/ecip0415/2004003130.html},
	Year = {2004},
	Bdsk-Url-1 = {http://www.loc.gov/catdir/toc/ecip0415/2004003130.html}}

@article{liuPearl2007,
	Abstract = {The desire to infer the evolutionary history of a
                  group of species should be more viable now that a
                  considerable amount of multilocus molecular data is
                  available. However, the current molecular
                  phylogenetic paradigm still reconstructs gene trees
                  to represent the species tree. Further, commonly
                  used methods of combining data, such as the
                  concatenation method, are known to be inconsistent
                  in some circumstances. In this paper, we propose a
                  Bayesian hierarchical model to estimate the
                  phylogeny of a group of species using multiple
                  estimated gene tree distributions, such as those
                  that arise in a Bayesian analysis of DNA sequence
                  data. Our model employs substitution models used in
                  traditional phylogenetics but also uses coalescent
                  theory to explain genealogical signals from species
                  trees to gene trees and from gene trees to sequence
                  data, thereby forming a complete stochastic model to
                  estimate gene trees, species trees, ancestral
                  population sizes, and species divergence times
                  simultaneously. Our model is founded on the
                  assumption that gene trees, even of unlinked loci,
                  are correlated due to being derived from a single
                  species tree and therefore should be estimated
                  jointly. We apply the method to two multilocus data
                  sets of DNA sequences. The estimates of the species
                  tree topology and divergence times appear to be
                  robust to the prior of the population size, whereas
                  the estimates of effective population sizes are
                  sensitive to the prior used in the analysis. These
                  analyses also suggest that the model is superior to
                  the concatenation method in fitting these data sets
                  and thus provides a more realistic assessment of the
                  variability in the distribution of the species tree
                  that may have produced the molecular information at
                  hand. Future improvements of our model and algorithm
                  should include consideration of other factors that
                  can cause discordance of gene trees and species
                  trees, such as horizontal transfer or gene
                  duplication.},
	Author = {Liu, L. and Pearl, D.K},
	Date-Added = {2009-08-24 12:15:56 +1200},
	Date-Modified = {2009-08-24 12:16:50 +1200},
	Doi = {10.1080/10635150701429982},
	Journal = {Syst Biol},
	Journal-Full = {Systematic biology},
	Mesh = {Algorithms; Animals; Bayes Theorem; Computational
                  Biology; Computer Simulation; Finches; Macaca;
                  Models, Genetic; Phylogeny; Sequence Analysis, DNA;
                  Time Factors},
	Month = {Jun},
	Number = {3},
	Pages = {504-14},
	Pmid = {17562474},
	Title = {Species trees from gene trees: reconstructing
                  Bayesian posterior distributions of a species
                  phylogeny using estimated gene tree distributions},
	Volume = {56},
	Year = {2007},
	Bdsk-Url-1 = {http://dx.doi.org/10.1080/10635150701429982}}

@article{liu2008est,
	Abstract = {Several techniques, such as concatenation and
                  consensus methods, are available for combining data
                  from multiple loci to produce a single statement of
                  phylogenetic relationships. However, when multiple
                  alleles are sampled from individual species, it
                  becomes more challenging to estimate relationships
                  at the level of species, either because
                  concatenation becomes inappropriate due to conflicts
                  among individual gene trees, or because the species
                  from which multiple alleles have been sampled may
                  not form monophyletic groups in the estimated
                  tree. We propose a Bayesian hierarchical model to
                  reconstruct species trees from multiple-allele,
                  multilocus sequence data, building on a recently
                  proposed method for estimating species trees from
                  single allele multilocus data. A two-step Markov
                  Chain Monte Carlo (MCMC) algorithm is adopted to
                  estimate the posterior distribution of the species
                  tree. The model is applied to estimate the posterior
                  distribution of species trees for two
                  multiple-allele datasets--yeast (Saccharomyces) and
                  birds (Manacus-manakins). The estimates of the
                  species trees using our method are consistent with
                  those inferred from other methods and genetic
                  markers, but in contrast to other species tree
                  methods, it provides credible regions for the
                  species tree. The Bayesian approach described here
                  provides a powerful framework for statistical
                  testing and integration of population genetics and
                  phylogenetics.},
	Author = {Liu, L. and Pearl, D.K and Brumfield, R.T and Edwards, S.V},
	Date-Added = {2009-08-24 12:15:39 +1200},
	Date-Modified = {2009-08-24 12:16:34 +1200},
	Doi = {10.1111/j.1558-5646.2008.00414.x},
	Journal = {Evolution},
	Journal-Full = {Evolution; international journal of organic evolution},
	Mesh = {Algorithms; Alleles; Animals; Bayes Theorem; Birds;
                  Computer Simulation; Evolution; Markov Chains;
                  Models, Genetic; Models, Statistical; Models,
                  Theoretical; Monte Carlo Method; Phylogeny;
                  Saccharomyces cerevisiae; Sequence Analysis, DNA;
                  Species Specificity},
	Month = {Aug},
	Number = {8},
	Pages = {2080-91},
	Pmid = {18462214},
	Title = {Estimating species trees using multiple-allele DNA sequence data},
	Volume = {62},
	Year = {2008},
	Bdsk-Url-1 = {http://dx.doi.org/10.1111/j.1558-5646.2008.00414.x}}

@article{wilson1998gim,
	Abstract = {Ease and accuracy of typing, together with high
                  levels of polymorphism and widespread distribution
                  in the genome, make microsatellite (or short tandem
                  repeat) loci an attractive potential source of
                  information about both population histories and
                  evolutionary processes. However, microsatellite data
                  are difficult to interpret, in particular because of
                  the frequency of back-mutations. Stochastic models
                  for the underlying genetic processes can be
                  specified, but in the past they have been too
                  complicated for direct analysis. Recent developments
                  in stochastic simulation methodology now allow
                  direct inference about both historical events, such
                  as genealogical coalescence times, and evolutionary
                  parameters, such as mutation rates. A feature of the
                  Markov chain Monte Carlo (MCMC) algorithm that we
                  propose here is that the likelihood computations are
                  simplified by treating the (unknown) ancestral
                  allelic states as auxiliary parameters. We
                  illustrate the algorithm by analyzing microsatellite
                  samples simulated under the model. Our results
                  suggest that a single microsatellite usually does
                  not provide enough information for useful
                  inferences, but that several completely linked
                  microsatellites can be informative about some
                  aspects of genealogical history and evolutionary
                  processes. We also reanalyze data from a previously
                  published human Y chromosome microsatellite study,
                  finding evidence for an effective population size
                  for human Y chromosomes in the low thousands and a
                  recent time since their most recent common ancestor:
                  the 95% interval runs from approximately 15, 000 to
                  130,000 years, with most likely values around 30,000
                  years.},
	Address = {School of Biological Sciences, Queen Mary and
                  Westfield College, University of London, London E1
                  4NS, England.},
	Author = {Wilson, IJ and Balding, DJ},
	Crdt = {1998/09/02 00:00},
	Da = {19981105},
	Date = {1998 Sep},
	Date-Added = {2009-03-15 13:23:04 +1300},
	Date-Modified = {2009-03-15 13:23:57 +1300},
	Dcom = {19981105},
	Edat = {1998/09/02},
	Issn = {0016-6731 (Print)},
	Jid = {0374636},
	Journal = {Genetics},
	Jt = {Genetics},
	Language = {eng},
	Lr = {20081120},
	Mh = {*Genetics, Population; Humans; *Microsatellite Repeats; Models, Genetic; Mutation; *Pedigree; Y Chromosome},
	Mhda = {1998/09/02 00:01},
	Month = {Sep},
	Number = {1},
	Oid = {NLM: PMC1460328},
	Own = {NLM},
	Pages = {499--510},
	Pl = {UNITED STATES},
	Pmc = {PMC1460328},
	Pmid = {9725864},
	Pst = {ppublish},
	Pt = {Journal Article; Research Support, Non-U.S. Gov't},
	Sb = {IM},
	Status = {MEDLINE},
	Title = {Genealogical inference from microsatellite data.},
	Volume = {150},
	Year = {1998}}

@inbook{zuckerkandl65,
	Address = {New York},
	Author = {E. Zuckerkandl and L. Pauling},
	Booktitle = {Evolving Genes and Proteins},
	Date-Added = {2009-03-14 23:41:43 +1300},
	Date-Modified = {2009-03-14 23:41:43 +1300},
	Editors = {V. Bryson and H. J. Vogel},
	Pages = {97--166},
	Publisher = {Academic Press},
	Title = {Evolutionary divergence and convergence in proteins},
	Year = {1965}}

@book{darwin1859,
	Address = {London},
	Annote = {LDR    00679cam  2200217u  4500
001    9612705
005    20030604092914.0
008    821207s1859    enka          000 0 eng  
035    \$9(DLC)   06017473
906    \$a0\$bcbc\$cpremunv\$du\$encip\$f19\$gy-gencatlg
010    \$a   06017473 
040    \$aDLC\$cCarP\$dDLC
050 00 \$aQH365\$b.O2 1859
100 1  \$aDarwin, Charles,\$d1809-1882.
245 10 \$aOn the origin of species by means of natural selection,
260    \$aLondon,\$bJ. Murray,\$c1859.
300    \$aix, [1], 502 p.\$bfold. diagr.\$c20 cm.
650  0 \$aEvolution.
650  0 \$aEvolution (Biology)
650  0 \$aNatural selection.
991    \$bc-GenColl\$hQH365\$i.O2 1859\$tCopy 1\$wPREM
},
	Author = {Darwin, Charles},
	Call-Number = {QH365},
	Date-Added = {2009-03-14 23:32:54 +1300},
	Date-Modified = {2009-03-14 23:33:26 +1300},
	Genre = {Evolution},
	Library-Id = {06017473},
	Publisher = {J. Murray},
	Title = {On the origin of species by means of natural selection},
	Year = {1859}}

@article{lam1936psp,
	Author = {Lam, HJ},
	Journal = {Acta Biotheoretica},
	Number = {3},
	Pages = {153--194},
	Publisher = {Springer},
	Title = {{Phylogenetic symbols, past and present}},
	Volume = {2},
	Year = {1936}}

@article{fitch1967cpt,
	Author = {Fitch, W.M. and Margoliash, E.},
	Journal = {Science},
	Number = {3760},
	Pages = {279--284},
	Title = {{Construction of Phylogenetic Trees}},
	Volume = {155},
	Year = {1967}}

@article{mau1999bpi,
	Author = {Mau, B. and Newton, M.A. and Larget, B.},
	Journal = {Biometrics},
	Number = {1},
	Pages = {1--12},
	Publisher = {Blackwell Synergy},
	Title = {{Bayesian Phylogenetic Inference via Markov Chain
                  Monte Carlo Methods}},
	Volume = {55},
	Year = {1999}}

@article{kubatko2007ipe,
	Author = {Kubatko, L.S.},
	Journal = {Systematic Biology},
	Number = {1},
	Pages = {17--24},
	Publisher = {Taylor \& Francis},
	Title = {{Inconsistency of Phylogenetic Estimates from
                  Concatenated Data under Coalescence}},
	Volume = {56},
	Year = {2007}}

@article{arvestad2003bgs,
	Author = {Arvestad, L. and Berglund, AC and Lagergren, J. and
                  Sennblad, B.},
	Journal = {Bioinformatics},
	Number = {1},
	Pages = {7--15},
	Publisher = {Oxford University Press},
	Title = {{Bayesian gene/species tree reconciliation and
                  orthology analysis using MCMC}},
	Volume = {19},
	Year = {2003}}

@article{wilson2003idd,
	Author = {Wilson, I.J. and Weale, M.E. and Balding, D.J.},
	Journal = {Journal of the Royal Statistical Society: Series A
                  (Statistics in Society)},
	Number = {2},
	Pages = {155--188},
	Publisher = {Blackwell Synergy},
	Title = {{Inferences from DNA data: population histories,
                  evolutionary processes and forensic match
                  probabilities}},
	Volume = {166},
	Year = {2003}}

@article{maddison1997gts,
	Author = {Maddison, W.P.},
	Journal = {Syst. Biol},
	Number = {3},
	Pages = {523--536},
	Publisher = {JSTOR},
	Title = {{Gene trees in species trees}},
	Volume = {46},
	Year = {1997}}

@article{goodman1979fgl,
	Author = {Goodman, M. and Czelusniak, J. and Moore, G.W. and
                  Romero-Herrera, AE and Matsuda, G.},
	Journal = {Syst. Zool},
	Number = {2},
	Pages = {132--163},
	Publisher = {JSTOR},
	Title = {{Fitting the gene lineage into its species lineage, a
                  parsimony strategy illustrated by cladograms
                  constructed from globin sequences}},
	Volume = {28},
	Year = {1979}}

@article{edwards2007hrs,
	Author = {Edwards, S.V. and Liu, L. and Pearl, D.K.},
	Journal = {Proceedings of the National Academy of Sciences},
	Number = {14},
	Pages = {5936},
	Publisher = {National Acad Sciences},
	Title = {{High-resolution species trees without concatenation}},
	Volume = {104},
	Year = {2007}}

@article{rannala2003bes,
	Author = {Rannala, B. and Yang, Z.},
	Journal = {Genetics},
	Number = {4},
	Pages = {1645--1656},
	Publisher = {Genetics Soc America},
	Title = {{Bayes Estimation of Species Divergence Times and
                  Ancestral Population Sizes Using DNA Sequences From
                  Multiple Loci}},
	Volume = {164},
	Year = {2003}}

@article{degnan2006dst,
	Author = {Degnan, J.H. and Rosenberg, N.A.},
	Journal = {PLoS Genet},
	Number = {5},
	Pages = {e68},
	Title = {{Discordance of species trees with their most likely
                  gene trees}},
	Volume = {2},
	Year = {2006}}

@article{pamilo1988rbg,
	Author = {Pamilo, P. and M. Nei},
	Journal = {Molecular Biology and Evolution},
	Number = {5},
	Pages = {568--583},
	Publisher = {SMBE},
	Title = {{Relationships between gene trees and species trees}},
	Volume = {5},
	Year = {1988}}

@article{tajima1983erd,
	Author = {Tajima, F.},
	Journal = {Genetics},
	Number = {2},
	Pages = {437--460},
	Publisher = {Genetics Soc America},
	Title = {{evolutionary relationship of dna sequences in finite
                  populations}},
	Volume = {105},
	Year = {1983}}

@article{belfiore2008multilocus,
  title={{Multilocus phylogenetics of a rapid radiation in the genus Thomomys (Rodentia: Geomyidae)}},
  author={Belfiore, N.M. and Liu, L. and Moritz, C.},
  journal={Systematic Biology},
  volume={57},
  number={2},
  pages={294},
  year={2008}
}

@article{BEAST,
	Abstract = {BACKGROUND: The evolutionary analysis of molecular
                  sequence variation is a statistical enterprise. This
                  is reflected in the increased use of probabilistic
                  models for phylogenetic inference, multiple sequence
                  alignment, and molecular population genetics. Here
                  we present BEAST: a fast, flexible software
                  architecture for Bayesian analysis of molecular
                  sequences related by an evolutionary tree. A large
                  number of popular stochastic models of sequence
                  evolution are provided and tree-based models
                  suitable for both within- and between-species
                  sequence data are implemented. RESULTS: BEAST
                  version 1.4.6 consists of 81000 lines of Java source
                  code, 779 classes and 81 packages. It provides
                  models for DNA and protein sequence evolution,
                  highly parametric coalescent analysis, relaxed clock
                  phylogenetics, non-contemporaneous sequence data,
                  statistical alignment and a wide range of options
                  for prior distributions. BEAST source code is
                  object-oriented, modular in design and freely
                  available at http://beast-mcmc.googlecode.com/ under
                  the GNU LGPL license. CONCLUSION: BEAST is a
                  powerful and flexible evolutionary analysis package
                  for molecular sequence variation. It also provides a
                  resource for the further development of new models
                  and statistical methods of evolutionary analysis.},
	Address = {Bioinformatics Institute, University of Auckland, Auckland, New Zealand. alexei@cs.auckland.ac.nz},
	Au = {Drummond, AJ and Rambaut, A},
	Author = {Drummond, A.J and Rambaut, A},
	Da = {20080215},
	Date-Added = {2008-08-28 23:02:35 +0100},
	Date-Modified = {2008-08-28 23:02:53 +0100},
	Dcom = {20080225},
	Dep = {20071108},
	Doi = {10.1186/1471-2148-7-214},
	Edat = {2007/11/13 09:00},
	Gr = {United Kingdom Wellcome Trust},
	Issn = {1471-2148 (Electronic)},
	Jid = {100966975},
	Journal = {BMC Evol Biol},
	Jt = {BMC evolutionary biology},
	Language = {eng},
	Mh = {Bayes Theorem; Computational Biology/*methods; Computer
                  Simulation; *Evolution, Molecular; Models, Genetic;
                  *Models, Statistical; *Phylogeny; Sequence Analysis,
                  DNA; *Software},
	Mhda = {2008/02/26 09:00},
	Own = {NLM},
	Pages = {214},
	Phst = {2007/10/16 {$[$}received{$]$}; 2007/11/08 {$[$}accepted{$]$}; 2007/11/08 {$[$}aheadofprint{$]$}},
	Pii = {1471-2148-7-214},
	Pl = {England},
	Pmc = {PMC2247476},
	Pmid = {17996036},
	Pst = {epublish},
	Pt = {Comparative Study; Journal Article; Research Support, Non-U.S. Gov't},
	Pubm = {Electronic},
	Sb = {IM},
	So = {BMC Evol Biol. 2007 Nov 8;7:214.},
	Stat = {MEDLINE},
	Title = {BEAST: Bayesian evolutionary analysis by sampling trees.},
	Volume = {7},
	Year = {2007},
	Bdsk-Url-1 = {http://dx.doi.org/10.1186/1471-2148-7-214}}

@article{heled2008bip,
	Author = {Heled, J. and Drummond, A.J.},
	Journal = {BMC Evolutionary Biology},
	Number = {1},
	Pages = {289},
	Title = {{Bayesian inference of population size history from multiple loci}},
	Volume = {8},
	Year = {2008}}

@article{18851752,
	Abstract = {The explosive growth of genomic data provides an
                  opportunity to make increased use of protein markers
                  for phylogenetic inference. We have developed an
                  automated pipeline for phylogenomic analysis
                  (AMPHORA) that overcomes the existing bottlenecks
                  limiting large-scale protein phylogenetic
                  inference. We demonstrated its high throughput
                  capabilities and high quality results by
                  constructing a genome tree of 578 bacterial species
                  and by assigning phylotypes to 18,607 protein
                  markers identified in metagenomic data collected
                  from the Sargasso Sea.},
	Author = {Wu, M. and Eisen, J.},
	Doi = {10.1186/gb-2008-9-10-r151},
	Issn = {1465-6906},
	Journal = {Genome Biology},
	Number = {10},
	Pages = {R151},
	Pubmedid = {18851752},
	Title = {A simple, fast, and accurate method of phylogenomic inference},
	Url = {http://genomebiology.com/2008/9/10/R151},
	Volume = {9},
	Year = {2008},
	Bdsk-Url-1 = {http://genomebiology.com/2008/9/10/R151},
	Bdsk-Url-2 = {http://dx.doi.org/10.1186/gb-2008-9-10-r151}}

@misc{huelsenbeck2001mbi,
	Author = {Huelsenbeck, J.P. and Ronquist, F.},
	Journal = {Bioinformatics},
	Number = {8},
	Pages = {754--755},
	Publisher = {Oxford Univ Press},
	Title = {{MRBAYES: Bayesian inference of phylogenetic trees}},
	Volume = {17},
	Year = {2001}}

@article{Griffiths,
	Adsnote = {Provided by the Smithsonian/NASA Astrophysics Data System},
	Adsurl = {http://adsabs.harvard.edu/abs/1994RSPTB.344..403G},
	Author = {{Griffiths}, R.C. and {Tavare}, S.},
	Journal = {Royal Society of London Philosophical Transactions Series B},
	Month = jun,
	Pages = {403-410},
	Title = {{Sampling Theory for Neutral Alleles in a Varying Environment}},
	Volume = 344,
	Year = 1994}

@article{heled2008bayesian,
	Author = {Heled, J. and Drummond, A.J.},
	Journal = {BMC Evolutionary Biology},
	Number = {1},
	Pages = {289},
	Publisher = {BioMed Central Ltd},
	Title = {{Bayesian inference of population size history from
                  multiple loci}},
	Volume = {8},
	Year = {2008}}

@article{gernhard2008conditioned,
	Author = {Gernhard, T.},
	Journal = {Journal of Theoretical Biology},
	Number = {4},
	Pages = {769--778},
	Publisher = {Elsevier},
	Title = {{The conditioned reconstructed process}},
	Volume = {253},
	Year = {2008}}

@article{kuhner1994simulation,
	Author = {Kuhner, M.K. and Felsenstein, J.},
	Journal = {Molecular Biology and Evolution},
	Number = {3},
	Pages = {459--468},
	Publisher = {Chicago, Ill.: University of Chicago Press, c1983-},
	Title = {{A simulation comparison of phylogeny algorithms
                  under equal and unequal evolutionary rates}},
	Volume = {11},
	Year = {1994}}

@article{felsenstein1981evolutionary,
	Author = {Felsenstein, J.},
	Journal = {Journal of molecular evolution},
	Number = {6},
	Pages = {368--376},
	Publisher = {Springer},
	Title = {{Evolutionary trees from DNA sequences: a maximum
                  likelihood approach}},
	Volume = {17},
	Year = {1981}}

@article{kaj2003coalescent,
	Author = {Kaj, I. and Krone, S.M.},
	Journal = {Journal of Applied Probability},
	Pages = {33--48},
	Publisher = {Applied Probability Trust},
	Title = {{The coalescent process in a population with
                  stochastically varying size}},
	Year = {2003}}

@article{edwards2009new,
  title={{Is a new and general theory of molecular systematics
                  emerging?}},
  author={Edwards, S.V. and Rausher, M.},
  journal={Evolution},
  volume={63},
  number={1},
  pages={1--19},
  year={2009},
  publisher={BioOne}
}

@article{crandall1995j,
  title={{J. Avise., Molecular Markers, Natural History and
                  Evolution}},
  author={Crandall, K.A.},
  journal={Systematic Biology},
  volume={44},
  number={1},
  pages={117},
  year={1995}
}


@article{petren1999phylogeny,
  title={{A phylogeny of Darwin's finches based on microsatellite DNA
                  length variation}},
  author={Petren, K. and Grant, B.R. and Grant, P.R.},
  journal={Proceedings: Biological Sciences},
  volume={266},
  number={1417},
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}


@article{boag1981intense,
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                  finches (Geospizinae) in the Galapagos}},
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@article{liu2008estimating,
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                  data}},
  author={Liu, L. and Pearl, D.K. and Brumfield, R.T. and Edwards,
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}

@book{orel1996gregor,
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}

@article{drummond2006relaxed,
  title={{Relaxed phylogenetics and dating with confidence}},
  author={Drummond, AJ and Ho, SYW and Phillips, MJ and Rambaut, A.},
  journal={PLoS Biol},
  volume={4},
  number={5},
  pages={e88},
  year={2006}
}
@article{hey2004multilocus,
  title={{Multilocus methods for estimating population sizes,
                  migration rates and divergence time, with
                  applications to the divergence of Drosophila
                  pseudoobscura and D. persimilis}},
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  journal={Genetics},
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  pages={747--760},
  year={2004},
  publisher={Genetics Soc America}
}
@article{pritchard2000inference,
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                  data}},
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  pages={945--959},
  year={2000},
  publisher={Genetics Soc America}
}

@article{huelsenbeck2007inference,
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  author={Huelsenbeck, J.P. and Andolfatto, P.},
  journal={Genetics},
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  number={4},
  pages={1787},
  year={2007},
  publisher={Genetics Society of America}
}


@article{glor2004partial,
  title={{Partial island submergence and speciation in an adaptive
                  radiation: a multilocus analysis of the Cuban green
                  anoles}},
  author={Glor, R.E. and Gifford, M.E. and Larson, A. and Losos,
                  J.B. and Schettino, L.R. and Lara, A.R.C. and
                  Jackman, T.R.},
  journal={Proceedings of the Royal Society of London, Series B:
                  Biological Sciences},
  volume={271},
  number={1554},
  pages={2257--2265},
  year={2004}
}
@article{meyer1993phylogenetic,
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  pages={279--279},
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}

@article{das2004ips,
	Author = {Das, A. and Mohanty, S. and Stephan, W.},
	Journal = {Genetics},
	Number = {4},
	Pages = {1975--1985},
	Publisher = {Genetics Soc America},
	Title = {{Inferring the Population Structure and Demography of
                  Drosophila ananassae From Multilocus Data}},
	Volume = {168},
	Year = {2004}}


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                  Markov chain Monte Carlo methods in population
                  genetics}},
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  volume={104},
  number={8},
  pages={2785},
  year={2007},
  publisher={National Acad Sciences}
}

@misc{sato1999phylogeny,
  title={{Phylogeny of Darwin's finches as revealed by mtDNA
                  sequences}},
  author={Sato, A. and O'hUigin, C. and Figueroa, F. and Grant,
                  P.R. and Grant, B.R. and Tichy, H. and Klein, J.},
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  year={1999},
  publisher={National Acad Sciences}
}

@article{rokas2003genome,
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                  molecular phylogenies}},
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  journal={Nature},
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  number={6960},
  pages={798--804},
  year={2003},
  publisher={Nature Publishing Group}
}

@article{pluzhnikov1996optimal,
  title={{Optimal sequencing strategies for surveying molecular
                  genetic diversity}},
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}

@article{JosephFelsenstein03012006,
	Abstract = {A computer simulation study has been made of the
                  accuracy of estimates of {Theta} = 4Ne{micro} from a
                  sample from a single isolated population of finite
                  size. The accuracies turn out to be well predicted
                  by a formula developed by Fu and Li, who used
                  optimistic assumptions. Their formulas are restated
                  in terms of accuracy, defined here as the reciprocal
                  of the squared coefficient of variation. This should
                  be proportional to sample size when the entities
                  sampled provide independent information. Using these
                  formulas for accuracy, the sampling strategy for
                  estimation of {Theta} can be investigated. Two
                  models for cost have been used, a cost-per-base
                  model and a cost-per-read model. The former would
                  lead us to prefer to have a very large number of
                  loci, each one base long. The latter, which is more
                  realistic, causes us to prefer to have one read per
                  locus and an optimum sample size which declines as
                  costs of sampling organisms increase. For realistic
                  values, the optimum sample size is 8 or fewer
                  individuals. This is quite close to the results
                  obtained by Pluzhnikov and Donnelly for a
                  cost-per-base model, evaluating other estimators of
                  {Theta}. It can be understood by considering that
                  the resources spent collecting larger samples
                  prevent us from considering more loci. An
                  examination of the efficiency of Watterson's
                  estimator of {Theta} was also made, and it was found
                  to be reasonably efficient when the number of
                  mutants per generation in the sequence in the whole
                  population is less than 2.5.  },
	Author = {Felsenstein, J.},
	Doi = {10.1093/molbev/msj079},
	Eprint = {http://mbe.oxfordjournals.org/cgi/reprint/23/3/691.pdf},
	Journal = {Mol Biol Evol},
	Number = {3},
	Pages = {691-700},
	Title = {{Accuracy of Coalescent Likelihood Estimates: Do We
                  Need More Sites, More Sequences, or More Loci?}},
	Url = {http://mbe.oxfordjournals.org/cgi/content/abstract/23/3/691},
	Volume = {23},
	Year = {2006},
	Bdsk-Url-1 = {http://mbe.oxfordjournals.org/cgi/content/abstract/23/3/691},
	Bdsk-Url-2 = {http://dx.doi.org/10.1093/molbev/msj079}}

@article{maddison2006inferring,
  title={{Inferring phylogeny despite incomplete lineage sorting}},
  author={Maddison, W.P. and Knowles, L.L.},
  journal={Systematic Biology},
  volume={55},
  number={1},
  pages={21},
  year={2006}
}
	

@article{schierup2000consequences,
  title={{Consequences of recombination on traditional phylogenetic
                  analysis}},
  author={Schierup, M.H. and Hein, J.},
  journal={Genetics},
  volume={156},
  number={2},
  pages={879--891},
  year={2000},
  publisher={Genetics Soc America}
}


@article{leache2009species,
  title={{Species Tree Discordance Traces to Phylogeographic Clade
                  Boundaries in North American Fence Lizards
                  (Sceloporus)}},
  author={Leache, A.D.},
  journal={Systematic Biology},
  year={2009},
  Doi={10.1093/sysbio/syp057}
}

% Review

% We review recent models to estimate phylogenetic trees under the multispecies coalescent.
@article{liu2009coalescent,
  title={{Coalescent methods for estimating phylogenetic trees}},
  author={Liu, L. and Yu, L. and Kubatko, L. and Pearl, D.K. and Edwards, S.V.},
  journal={Molecular Phylogenetics and Evolution},
  volume={53},
  number={1},
  pages={320--328},
  year={2009},
  publisher={Elsevier}
}

% Review of the problem of lineage sorting, defines multispecies coalescent etc
@article{degnan2009gene,
  title={{Gene tree discordance, phylogenetic inference and the
                  multispecies coalescent}},
  author={Degnan, J.H. and Rosenberg, N.A.},
  journal={Trends in Ecology \& Evolution},
  volume={24},
  number={6},
  pages={332--340},
  year={2009},
  publisher={Elsevier}
}

% Methods

% ML, needs the user to input trees, theta (assumed constant for
% all branches) and clock rate per loci. is that useful at all?

@article{kubatko2009stem,
  title={{STEM: species tree estimation using maximum likelihood for
                  gene trees under coalescence}},
  author={Kubatko, L.S. and Carstens, B.C. and Knowles, L.L.},
  journal={Bioinformatics},
  volume={25},
  number={7},
  pages={971},
  year={2009},
  publisher={Oxford Univ Press}
}

% (STAR) and (STEAC), inferring Species trees from coalescence Summary statistics.
@article{liu2009estimating,
  title={{Estimating species phylogenies using coalescence times among
                  sequences}},
  author={Liu, L. and Yu, L. and Pearl, D.K. and Edwards, S.V.},
  journal={Systematic Biology},
  year={2009},
  Doi={10.1093/sysbio/syp031}
}


% Consensus methods for known gene trees as number of loci goes to infinity

@article{degnan2009properties,
  title={{Properties of consensus methods for inferring species trees
                  from gene trees}},
  author={Degnan, J.H. and DeGiorgio, M. and Bryant, D. and Rosenberg,
                  N.A.},
  journal={Systematic Biology},
  volume={58},
  number={1},
  pages={35},
  year={2009}
}

% Recovery of species trees using stem - various loci/individuals schems, 8 species
@article{mccormack2009maximum,
  title={{Maximum Likelihood Estimates of Species Trees: How Accuracy
                  of Phylogenetic Inference Depends upon the
                  Divergence History and Sampling Design}},
  author={McCormack, J.E. and Huang, H. and Knowles, L.L.},
  journal={Systematic Biology},
  year={2009},
  Doi={10.1093/sysbio/syp045}
}

%AGT

% another BEST promo. picking trees in the "anomalous zone" and recovery
% via concatanation UPGMA, NJ etc.

@article{liu2009phylogenetic,
  title={{Phylogenetic analysis in the anomaly zone}},
  author={Liu, L. and Edwards, S.V.},
  journal={Systematic Biology},
  year={2009},
  volume={58},
  pages={452--460}
}

% 4 taxa Species tree, 1 loci PAUP, quantify effect of coalescent
% vs. sequence stocasticity. AGT. I think their conclusion holds only
% because they use 1 individual 1 loci and the gene topology to estimate
% the species tree

@article{huang2009danger,
  title={{What Is the Danger of the Anomaly Zone for Empirical
                  Phylogenetics?}},
  author={Huang, H. and Knowles, L.L.},
  journal={Systematic Biology},
  year={2009},
  Doi={10.1093/sysbio/syp047}
}


% bla bla paradigm shift bla 
@article{knowles2009estimating,
  title={{Estimating Species Trees: Methods of Phylogenetic Analysis
                  When There Is Incongruence across Genes}},
  author={Knowles, L.L.},
  journal={Systematic Biology},
  year={2009},
  Doi={10.1093/sysbio/syp061}
}

@article{liu2008best,
  title={{BEST: Bayesian estimation of species trees under the coalescent model}},
  author={Liu, L.},
  journal={Bioinformatics},
  volume={24},
  number={21},
  pages={2542},
  year={2008},
  publisher={Oxford Univ Press}
}
