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David R. Maddison

Bio: David R. Maddison is an academic researcher from Oregon State University. The author has contributed to research in topics: Monophyly & Subgenus. The author has an hindex of 29, co-authored 78 publications receiving 12366 citations. Previous affiliations of David R. Maddison include University of Arizona & University of Alberta.


Papers
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Book
01 Jan 2005
TL;DR: MacClade is a computer program that provides theory and tools for the graphic and interactive analysis of molecular and morphological data, phylogeny, and character evolution, yet its ease of use allows beginning students to grasp phylogenetic principles in an interactive environment.
Abstract: MacClade is a computer program, with accompanying manual, that provides theory and tools for the graphic and interactive analysis of molecular and morphological data, phylogeny, and character evolution. Systematists and other evolutionary biologists can use its flexible tools to analyse phylogeny and character evolution, yet its ease of use allows beginning students to grasp phylogenetic principles in an interactive environment.

5,175 citations

Book
01 Nov 1992
TL;DR: Part I Introducing MacClade: introduction - a tutorial overview of MacClades and an introduction to phylogeny reconstructing character evolution using parsimony stratigraphic parsimony.
Abstract: Part I Introducing MacClade: introduction - a tutorial overview of MacClade. Part II Phylogenetic theory: a phylogenetic perspective an introduction to phylogeny reconstructing character evolution using parsimony stratigraphic parsimony Part III Using MacClade: using MacClade on your Macintosh managing data files importing and exporting text files the data editor assumptions about characters trees and tree manipulation tracing character evolution basic tree and character statistics charting tree and character statistics continuous characters patterns of correlated character evolution generating random data and random trees using MacClade with molecular data recording your work. Appendix: file format.

1,472 citations

Journal ArticleDOI
TL;DR: Methods that use outgroups in the reconstruction of phylogeny are described and evaluated by the criterion of parsimony, and algorithms and rules are presented that find the most parsimonious estimates of ancestral states for binary and multistate characters when outgroup relationships are well resolved.
Abstract: -Methods that use outgroups in the reconstruction of phylogeny are described and evaluated by the criterion of parsimony. By considering the character states and relationships of outgroups, one can estimate the states ancestral for a study group or ingroup, even when several character states are found among the outgroups. Algorithms and rules are presented that find the most parsimonious estimates of ancestral states for binary and multistate characters when outgroup relationships are well resolved. Other rules indicate the extent to which uincertainty about outgroup relationships leads to uncertainty about the ancestral states. The algorithms and rules are based on "simple parsimony" in that convergences and reversals are counted equally. After parsimony is measured locally among the outgroups to estimate ancestral states, parsimony is measured locally within the ingroup, given the ancestral states, to find the ingroup cladogram. This two-step procedure is shown to find the ingroup cladograms that are most parsimonious globally; that is, most parsimonious when parsimony is measured simultaneously over the ingroup and outgroups. However, the two-step procedure is guaranteed to achieve global parsimony only when: (a) outgroup relationships are sufficiently resolved beforehand; (b) outgroup analysis is taken to indicate the state not in the most recent common ancestor of the ingroup, but in a more distant ancestor; and (c) ancestral states are considered while the ingroup is being resolved, not merely added afterward to root an unrooted network. The criterion of global parsimony is then applied to evaluate procedures used when outgroup relationships are poorly resolved. The procedure that chooses as ancestral the state occurring most commonly among the outgroups can sometimes yield cladograms that are not globally parsimonious. By the criterion of global parsimony, the best procedure is one that simultaneously resolves the outgroups and ingroup with the data at hand. Finally, simple parsimony can choose among competing hypotheses, but it often fails to indicate how much confidence can be placed in that choice. [Phylogeny reconstruction; cladistic methods; outgroup analysis; character polarity; parsimony.] This paper explores the use of outgroup analysis in phylogeny reconstruction. When reconstructing a phylogeny, a systematist asks: Given a group of organisms (the ingroup), what are the monophyletic subgroups? If the members of a subgroup share a character state that is derived within the group, the monophyly of this subgroup is corroborated (Hennig, 1966; Wiley, 1975). Hence, systematists attempting to infer phylogenies have sought methods for determining whether a given character state is derived (apomorphic) or ancestral (plesiomorphic). Many methods for assessing the evolutionary polarity of characters have been proposed, including outgroup analysis, ingroup analysis, the ontogenetic method, and the paleontological method. These approaches have been reviewed recently by Crisci and Stuessy (1980), de Jong (1980), Stevens (1980), Arnold (1981), Nelson and Platnick (1981), and others. The methods perhaps most widely accepted today are outgroup analysis and the ontogenetic method, the relative merits of which are still being debated (contrast Nelson [1978] and Patterson [1982] with Lundberg [1973], Wheeler [1981] and Voorzanger and van der Steen [1982]). In its simplest form, outgroup analysis can be summarized by the following rule (Watrous and Wheeler, 1981): For a given character with two or more states within a group, the state occurring in related groups is assumed to be the plesiomorphic state. This rule is inadequate, however, when characters vary among the related groups (the outgroups). Arnold (1981) and Farris (1982) have dealt with some cases of

1,117 citations

Journal ArticleDOI
TL;DR: In this article, the set of most parsimonious trees for a data matrix may include several distinct classes (islands) of trees, each one differing from the next by a single rearrangement of branches.
Abstract: The set of most-parsimonious trees for a data matrix may include several distinct classes (islands) of trees. An island is defined as a collection of trees, all less than a specified length, each tree connected to every other tree in the island through a series of trees, and each one differing from the next by a single rearrangement of branches. One advantage of this method of defining classes of trees is that islands are easily found by tree-searching programs. Multiple islands can be discovered by conducting many searches using a tree-searching program, each search beginning with a different tree. Among 37 data matrices examined, all 8 data matrices with two or more islands have retention indices less than 0.67. Trees are generally more similar within islands than among islands, as judged by analysis of partition metric distances between trees. As a consequence, trees in different islands may have different implications for character evolution, and for this reason should be sought. (Parsimony; phylogeny; tree searching; opti- mization; multiple optima; islands of trees; character evolution.)

774 citations

Journal ArticleDOI
21 Dec 2007-Zootaxa
TL;DR: The Tree of Life Web Project (ToL) as discussed by the authors provides information on the Internet about our current knowledge of the evolutionary tree of life and associated information about characteristics and diversity of life on Earth.
Abstract: The Tree of Life Web Project (ToL) provides information on the Internet about our current knowledge of the evolutionary tree of life and associated information about characteristics and diversity of life on Earth. Development of this open-access, database-driven system began in 1994; its official release was in 1996. Core scientific content in the project is compiled collaboratively by more than 540 biologists, all experts in particular groups of organisms, from over 35 countries. Additional learning materials are contributed by over 200 students, teachers, and amateur scientists, while images, movies, and sounds are contributed by both of these groups and over 200 media-only contributors. Administration of the project follows a hierarchical, community-based model, with authors for different parts of the ToL chosen by the scientists working in that particular field. The goals of the project are to document all species on Earth, as well as all significant clades; to provide basic information about the phylogeny of life; to share this information with other databases and analytical tools; and to encourage understanding and appreciation for biodiversity, evolution, and the interrelationships of Earth's wealth of species. Here we provide an outline of the goals and history of the project; the current content, administration, architecture, contributors, and audience, the challenges we have faced, and the future of the project.

538 citations


Cited by
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Journal ArticleDOI
TL;DR: The program MRBAYES performs Bayesian inference of phylogeny using a variant of Markov chain Monte Carlo, and an executable is available at http://brahms.rochester.edu/software.html.
Abstract: Summary: The program MRBAYES performs Bayesian inference of phylogeny using a variant of Markov chain Monte Carlo. Availability: MRBAYES, including the source code, documentation, sample data files, and an executable, is available at http://brahms.biology.rochester.edu/software.html.

20,627 citations

Journal ArticleDOI
TL;DR: Version 5 implements a number of new features and analytical methods allowing extensive DNA polymorphism analyses on large datasets, including visualizing sliding window results integrated with available genome annotations in the UCSC browser.
Abstract: Motivation: DnaSP is a software package for a comprehensive analysis of DNA polymorphism data. Version 5 implements a number of new features and analytical methods allowing extensive DNA polymorphism analyses on large datasets. Among other features, the newly implemented methods allow for: (i) analyses on multiple data files; (ii) haplotype phasing; (iii) analyses on insertion/deletion polymorphism data; (iv) visualizing sliding window results integrated with available genome annotations in the UCSC browser. Availability: Freely available to academic users from: http://www.ub.edu/dnasp Contact: [email protected]

13,511 citations

Journal ArticleDOI
TL;DR: An overview of the statistical methods, computational tools, and visual exploration modules for data input and the results obtainable in MEGA is provided.
Abstract: With its theoretical basis firmly established in molecular evolutionary and population genetics, the comparative DNA and protein sequence analysis plays a central role in reconstructing the evolutionary histories of species and multigene families, estimating rates of molecular evolution, and inferring the nature and extent of selective forces shaping the evolution of genes and genomes. The scope of these investigations has now expanded greatly owing to the development of high-throughput sequencing techniques and novel statistical and computational methods. These methods require easy-to-use computer programs. One such effort has been to produce Molecular Evolutionary Genetics Analysis (MEGA) software, with its focus on facilitating the exploration and analysis of the DNA and protein sequence variation from an evolutionary perspective. Currently in its third major release, MEGA3 contains facilities for automatic and manual sequence alignment, web-based mining of databases, inference of the phylogenetic trees, estimation of evolutionary distances and testing evolutionary hypotheses. This paper provides an overview of the statistical methods, computational tools, and visual exploration modules for data input and the results obtainable in MEGA.

12,124 citations

Journal ArticleDOI
TL;DR: TreeView is a simple, easy to use phylogenetic tree viewing utility that runs under both MacOS (on Apple Macintosh computers) and under Microsoft Windows on Intel based computers, the two most common personal computers used by biologists.
Abstract: TreeView is a simple, easy to use phylogenetic tree viewing utility that runs under both MacOS (on Apple Macintosh computers) and under Microsoft Windows on Intel based computers, the two most common personal computers used by biologists. Some phylogeny programs, such as PAUP (Swofford, 1993) and MacClade (Maddison and Maddison, 1992) already provide excellent tree drawing and printing facilities, however at present these programs are restricted to Apple Macintosh computers. Furthermore, they require the user to load a data set before any trees can be displayed which is inconvenient if the user simply wants to view the trees. More portable programs, such as DRAWGRAM and DRAWTREE in the PHYLIP package (Felsenstein, 1993) can run on both MacOS and Windows computers, but make little, if any use of the graphical interface features available under those operating systems. TreeView runs as a native application on either MacOS or Windows computers, enables the user to use the standard fonts installed on their machine, their printer, and supports the relevant native graphics format (PICT and Windows metafile) for either creating graphics files or pasting pictures to other applications via the clipboard. The program also supports standard file operations, such as 'drag and drop' whereby dragging a file's icon onto the program opens that file. TreeView can read a range of tree file formats (see below) and can display trees in a range of styles (Fig. 1). Additional information, such as edge lengths and internal node labels can also be displayed. The order of the terminal taxa in the tree can be altered, and the tree can be rerooted. If the tree file contains more than one tree the user can view each tree in turn. The program can also save trees in a variety of file formats, so that it can be used to move trees between programs that use different file formats.

10,368 citations