Parsimony evolutionary

Phylogenetic analysis provides an evolutionary framework with which we can map the evolution of characters, including those pertinent to parasitism, that define the diversity and biology of extant flatworms, and from which ancestral conditions may be inferred. Alternative scenarios can be tested in terms of how parsimoniously they may map on to the evolutionary hypothesis to hand and through these... 

Although distance methods have certain advantages for the analysis of restriction site data, notably their computational efficiency, they also have an important disadvantage. By reducing the data to pairwise distances, important information on the evolutionary history of individual restriction sites is lost. In chloroplast DNA, for example, individual sites often evolve at very different rates. A parsimony analysis of 328 restriction site mutations shared among two or more taxa in a survey of 57 taxa from the sunflower family showed that 186 of the sites had only a single mutation, whereas 6 sites showed nine or more mutations.24 A conservative statistical... 

Three different parsimony methods have been used for the analysis of restriction site data Wagner parsimony,25 Dollo parsimony,26 and weighted parsimony or generalized parsimony.27 As the names suggest, they all invoke a parsimony principle to select the best tree (or trees) from the set of all possible trees. Specifically, the trees selected are those that require the minimum amount of evolutionary change. The methods differ from one another in how the amount of evolutionary change is calculated. 

Parsimony Selects phylogeny that minimizes number of evolutionary changes for data set. Approach relies on phylogenetically informative characters (i.e., those with two or more states shared by two or more taxa) 1... 

In view of such developments, it is not surprising that there have been several attempts in 1985-1989 to reconsider the evolutionary relationships. The approach in many studies has been to construct parsimony trees using methods and computer programs based essentially on the maximum parsimony methods of Farris (1970, 1972) or Fitch and Mar-... 

Nevertheless, this last mentioned relationship is clearly well established A specific relationship between the extreme halophiles and the Methanomicrobiales can be demonstrated by a variety of analyses of 16S rRNA sequences - any number of variations on evolutionary distance analysis, parsimony analysis, signature analysis [48,62] and maximum likelihood analysis (G.J. Olsen, personal communication). More importantly, the relationship is also readily given by analysis of 23 S rRNA sequences [62],... 

Distance matrix methods simply count the number of differences between two sequences. This number is referred to as the evolutionary distance, and its exact size depends on the evolutionary model used. The actual tree is then computed from the matrix of distance values by running a clustering algorithm that starts with the most similar sequences (i.e., those that have the shortest distance between them) or by trying to minimize the total branch length of the tree. The principle of maximum parsimony searches for a tree that requires the smallest number of changes to explain the differences observed among the taxa under study. 

There are several important philosophical differences between distance-based phylogenetic methods and character-based parsimony which should not be overlooked. First is the unappealing property of distance-based analyses that all information on evolutionary change is averaged into one number for each pair of taxa. Second, to paraphrase Swofford and Olsen (1990), the as stamptions involved in distance methods (such as additivity and clock-like evolution) are rarely evident or discussed and the justification of the algorithm itself often seems to be the objective of the study. On the contrary, in the case of methods will a well-defined optimality criterion such as parsimony, the objective is usually related to a (more or less) concrete set of assumptions. 

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