Literature DB >> 9787470

Phylogenetic information and experimental design in molecular systematics.

N Goldman1.   

Abstract

Despite the widespread perception that evolutionary inference from molecular sequences is a statistical problem, there has been very little attention paid to questions of experimental design. Previous consideration of this topic has led to little more than an empirical folklore regarding the choice of suitable genes for analysis, and to dispute over the best choice of taxa for inclusion in data sets. I introduce what I believe are new methods that permit the quantification of phylogenetic information in a sequence alignment. The methods use likelihood calculations based on Markov-process models of nucleotide substitution allied with phylogenetic trees, and allow a general approach to optimal experimental design. Two examples are given, illustrating realistic problems in experimental design in molecular phylogenetics and suggesting more general conclusions about the choice of genomic regions, sequence lengths and taxa for evolutionary studies.

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Year:  1998        PMID: 9787470      PMCID: PMC1689363          DOI: 10.1098/rspb.1998.0502

Source DB:  PubMed          Journal:  Proc Biol Sci        ISSN: 0962-8452            Impact factor:   5.349


  16 in total

1.  Sample size for a phylogenetic inference.

Authors:  G A Churchill; A von Haeseler; W C Navidi
Journal:  Mol Biol Evol       Date:  1992-07       Impact factor: 16.240

2.  Phylogenetic methods come of age: testing hypotheses in an evolutionary context.

Authors:  J P Huelsenbeck; B Rannala
Journal:  Science       Date:  1997-04-11       Impact factor: 47.728

3.  Inferring complex phylogenies.

Authors:  D M Hillis
Journal:  Nature       Date:  1996-09-12       Impact factor: 49.962

4.  Optimal sequencing strategies for surveying molecular genetic diversity.

Authors:  A Pluzhnikov; P Donnelly
Journal:  Genetics       Date:  1996-11       Impact factor: 4.562

5.  Effects of nucleotide sequence alignment on phylogeny estimation: a case study of 18S rDNAs of apicomplexa.

Authors:  D A Morrison; J T Ellis
Journal:  Mol Biol Evol       Date:  1997-04       Impact factor: 16.240

6.  Reconstruction of phylogenetic trees and estimation of divergence times under nonconstant rates of evolution.

Authors:  W H Li; K H Wolfe; J Sourdis; P M Sharp
Journal:  Cold Spring Harb Symp Quant Biol       Date:  1987

7.  Comparison of models for nucleotide substitution used in maximum-likelihood phylogenetic estimation.

Authors:  Z Yang; N Goldman; A Friday
Journal:  Mol Biol Evol       Date:  1994-03       Impact factor: 16.240

8.  A method for determining the position and size of optimal sequence regions for phylogenetic analysis.

Authors:  M J Martin; F González-Candelas; F Sobrino; J Dopazo
Journal:  J Mol Evol       Date:  1995-12       Impact factor: 2.395

9.  A simulation comparison of phylogeny algorithms under equal and unequal evolutionary rates.

Authors:  M K Kuhner; J Felsenstein
Journal:  Mol Biol Evol       Date:  1994-05       Impact factor: 16.240

10.  The spider monkey psi eta-globin gene and surrounding sequences: recent or ancient insertions of LINEs and SINEs?

Authors:  D H Fitch; C Mainone; J L Slightom; M Goodman
Journal:  Genomics       Date:  1988-10       Impact factor: 5.736

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  22 in total

1.  Increased taxon sampling is advantageous for phylogenetic inference.

Authors:  David D Pollock; Derrick J Zwickl; Jimmy A McGuire; David M Hillis
Journal:  Syst Biol       Date:  2002-08       Impact factor: 15.683

Review 2.  Genomic biodiversity, phylogenetics and coevolution in proteins.

Authors:  David D Pollock
Journal:  Appl Bioinformatics       Date:  2002

Review 3.  The impact of taxon sampling on phylogenetic inference: a review of two decades of controversy.

Authors:  Ahmed Ragab Nabhan; Indra Neil Sarkar
Journal:  Brief Bioinform       Date:  2011-03-23       Impact factor: 11.622

4.  Evolution of bacterial recombinase A (recA) in eukaryotes explained by addition of genomic data of key microbial lineages.

Authors:  Paulo G Hofstatter; Alexander K Tice; Seungho Kang; Matthew W Brown; Daniel J G Lahr
Journal:  Proc Biol Sci       Date:  2016-10-12       Impact factor: 5.349

5.  Estimating Bayesian Phylogenetic Information Content.

Authors:  Paul O Lewis; Ming-Hui Chen; Lynn Kuo; Louise A Lewis; Karolina Fučíková; Suman Neupane; Yu-Bo Wang; Daoyuan Shi
Journal:  Syst Biol       Date:  2016-05-06       Impact factor: 15.683

6.  More on the Best Evolutionary Rate for Phylogenetic Analysis.

Authors:  Seraina Klopfstein; Tim Massingham; Nick Goldman
Journal:  Syst Biol       Date:  2017-09-01       Impact factor: 15.683

7.  Measuring Phylogenetic Information of Incomplete Sequence Data.

Authors:  Tae-Kun Seo; Olivier Gascuel; Jeffrey L Thorne
Journal:  Syst Biol       Date:  2022-04-19       Impact factor: 9.160

8.  Excluding Loci With Substitution Saturation Improves Inferences From Phylogenomic Data.

Authors:  David A Duchêne; Niklas Mather; Cara Van Der Wal; Simon Y W Ho
Journal:  Syst Biol       Date:  2022-04-19       Impact factor: 9.160

9.  Evolutionary Rate Variation among Lineages in Gene Trees has a Negative Impact on Species-Tree Inference.

Authors:  Mezzalina Vankan; Simon Y W Ho; David A Duchêne
Journal:  Syst Biol       Date:  2022-02-10       Impact factor: 15.683

10.  Data mining approach identifies research priorities and data requirements for resolving the red algal tree of life.

Authors:  Heroen Verbruggen; Christine A Maggs; Gary W Saunders; Line Le Gall; Hwan Su Yoon; Olivier De Clerck
Journal:  BMC Evol Biol       Date:  2010-01-20       Impact factor: 3.260

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