Topic
Maximum parsimony
About: Maximum parsimony is a research topic. Over the lifetime, 2422 publications have been published within this topic receiving 180278 citations.
Papers published on a yearly basis
Papers
More filters
TL;DR: The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models, inferring ancestral states and sequences, and estimating evolutionary rates site-by-site.
Abstract: Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. Here, we announce the release of Molecular Evolutionary Genetics Analysis version 5 (MEGA5), which is a user-friendly software for mining online databases, building sequence alignments and phylogenetic trees, and using methods of evolutionary bioinformatics in basic biology, biomedicine, and evolution. The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models (nucleotide or amino acid), inferring ancestral states and sequences (along with probabilities), and estimating evolutionary rates site-by-site. In computer simulation analyses, ML tree inference algorithms in MEGA5 compared favorably with other software packages in terms of computational efficiency and the accuracy of the estimates of phylogenetic trees, substitution parameters, and rate variation among sites. The MEGA user interface has now been enhanced to be activity driven to make it easier for the use of both beginners and experienced scientists. This version of MEGA is intended for the Windows platform, and it has been configured for effective use on Mac OS X and Linux desktops. It is available free of charge from http://www.megasoftware.net.
39,110 citations
18,553 citations
01 Jan 2002
16,957 citations
Book•
15 Aug 2000
TL;DR: This chapter discusses the molecular basis of evolution, the evolution of organisms based on the fossil record, and the implications of these events for phylogenetic inference.
Abstract: 1. Molecular basis of evolution 2. Evolutionary changes of amino acid sequences 3. Evolutionary changes of DNA sequences 4. Synonymous and nonsynonymous nucleotide substitutions 5. Phylogenetic trees 6. Phylogenetic inference: Distance methods 7. Phylogenetic inference: Maximum parsimony methods 8. Phylogenetic inference: Maximum likelihood methods 9. Accuracies and statistical tests of phylogenetic trees 10. Molecular clocks and linearized trees 11. Ancestral nucleotide and amino acid sequences 12. Genetic polymorphism and evolution 13. Population trees from genetic markers 14. Perspectives Appendices A. Mathematical sumbols and notations B. Geological timescale C. Geological events in the Cenozoic and Meszoic eras D. Evolution of organisms based on the fossil record
5,629 citations
TL;DR: Phangorn is a package for phylogenetic reconstruction and analysis in the R language that offers the possibility of reconstructing phylogenies with distance based methods, maximum parsimony or maximum likelihood (ML) and performing Hadamard conjugation.
Abstract: Summary: phangorn is a package for phylogenetic reconstruction and analysis in the R language. Previously it was only possible to estimate phylogenetic trees with distance methods in R. phangorn, now offers the possibility of reconstructing phylogenies with distance based methods, maximum parsimony or maximum likelihood (ML) and performing Hadamard conjugation. Extending the general ML framework, this package provides the possibility of estimating mixture and partition models. Furthermore, phangorn offers several functions for comparing trees, phylogenetic models or splits, simulating character data and performing congruence analyses.
Availability: phangorn can be obtained through the CRAN homepage http://cran.r-project.org/web/packages/phangorn/index.html. phangorn is licensed under GPL 2.
Contact: rf.ueissuj.vns@peilhcsk.sualk
Supplementary information: Supplementary data are available at Bioinformatics online.
2,540 citations