Download Algorithms in Bioinformatics: 11th International Workshop, by Broňa Brejová, Michal Burger, Tomáš Vinař (auth.), Teresa M. PDF

By Broňa Brejová, Michal Burger, Tomáš Vinař (auth.), Teresa M. Przytycka, Marie-France Sagot (eds.)

This publication constitutes the refereed lawsuits of the eleventh foreign Workshop on Algorithms in Bioinformatics, WABI 2011, held in Saarbrücken, Germany, in September 2011.
The 30 papers provided have been rigorously reviewed and chosen from seventy seven submissions. They disguise features of algorithms in bioinformatics, computational biology and platforms biology.

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Additional info for Algorithms in Bioinformatics: 11th International Workshop, WABI 2011, Saarbrücken, Germany, September 5-7, 2011. Proceedings

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To model the third condition, we introduce binary variables ak,p , 1 ≤ k ≤ 2L, 1 ≤ p ≤ m, which indicate the allele at locus p of chromosome k. Note that for chromosomes k corresponding to initial parental genotypes, ak,p , 1 ≤ p ≤ m, is a constant rather than a variable. In addition to knowing from which genotype a chromosome originates, we also need to know from which of the two chromosomes of that parental genotype an allele comes. Therefore we define binary variable yk,p , 2n < k ≤ 2L, 1 ≤ p ≤ m, to be 1 if the allele at locus p of chromosome k comes from the lower chromosome of its originating genotype; conversely yk,p is 0 if the allele originates from the upper chromosome.

In case a pair of alleles at loci p and q of C1,· do not correspond to the same chromosome of D, we say that a crossover has occurred between loci p and q (see Figure 1). From the genetic map, the probability of having a crossover between any pair of loci can be inferred using for instance Haldane’s mapping function [5]. Let R be a m × m matrix containing all crossover probabilities. 5 for 1 ≤ p < q ≤ m. Let s = (ν(1), . . , ν(k)) be an ordered sequence of heterozygous loci in D. e. Pr[ D → C1,· ], is then as follows [10].

In all cases, the guide tree is on 200 taxa; except in the second line of the table, this was generated with Neighbor Joining, and had RF accuracy of 50% ± 3%. 6 In general, WTA voting tended to produce trees with higher RF accuracy than weighted-majority voting. In contrast, weighted-majority voting resulted in higher quartet accuracy, as we shall see in the next experiment. We see that there is a trade-off between the proportion of the inserted taxa and the RF accuracy. This is not surprising since incorrectly inserting a new taxon into the phylogeny can cause many splits to be incorrect.

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