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Parsimony, Phylogeny, and Genomics$
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Victor A. Albert

Print publication date: 2006

Print ISBN-13: 9780199297306

Published to Oxford Scholarship Online: September 2007

DOI: 10.1093/acprof:oso/9780199297306.001.0001

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Alignment, dynamic homology, and optimization

Alignment, dynamic homology, and optimization

(p.71) Chapter 5 Alignment, dynamic homology, and optimization
Parsimony, Phylogeny, and Genomics

Ward C. Wheeler

Oxford University Press

There are two properties that have been used to differentiate sequence data from other sorts of information: simplicity of states and length variation. Unlike complex anatomical features (e.g., limb or wing) that can express themselves in a myriad of forms, nucleotides exhibit only four conditions. Complexity and difference imply that states (e.g., presence/absence, or conditions) are not comparable across characters. Nucleotide states, on the other hand are identical no matter where they occur. Nucleotide sequences may also differ in length. These two aspects of molecular sequence data remove the complexity and positional information so often used in establishing primary homologies in anatomical systems. Two approaches have been developed to deal with the absence of preordained homologies and analyse sequence data. On one hand, methods have been devised to create the missing primary homology statements that are then analysed by standard techniques broadly referred to as multiple alignment. Traditionally, sequence data have undergone this pre-phylogenetic analysis step to permit familiar procedures akin to those used with anatomical characters. A second approach is to optimize directly sequence variation during cladogram searching. This methodology requires no notions of primary character homology or any global (topology-independent) homology statements whatsoever, other than that the compared sequences themselves be homologous.

Keywords:   nucleotides, multiple alignment, direct optimization, Needleman-Wunsch algorithm, implied alignment

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