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Download Comparative Genomics: RECOMB 2007 International Workshop, by Max A. Alekseyev (auth.), Glenn Tesler, Dannie Durand (eds.) PDF

By Max A. Alekseyev (auth.), Glenn Tesler, Dannie Durand (eds.)

This e-book constitutes the refereed complaints of the fifth RECOMB Comparative Genomics satellite tv for pc Workshop, RECOMB-CG 2007, held in San Diego, CA, united states, in September 2007.

The 14 revised complete papers provided have been conscientiously reviewed and chosen from 18 preliminary submissions. The papers deal with a huge number of facets and parts of the sector of comparative genomics, starting from quantitative discoveries approximately genome constitution to algorithms for comparative inference to theorems at the complexity of computational difficulties required for genome comparison.

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Extra resources for Comparative Genomics: RECOMB 2007 International Workshop, RECOMB-CG 2007, San Diego, CA, USA, September 16-18, 2007. Proceedings

Example text

However, computing the inversion distance is NP-hard in the unsigned case [9]. The HP algorithm is based on the breakpoint graph (Fig 1). We assume without loss of generality that one permutation is the identity. We represent gene i by two vertices, −i and +i, connected by an edge. The edge is oriented from +i to −i when gene i is positive, but oriented in the reverse direction when it is negative. Two additional vertices 0 and n + 1 are also added. These vertices can be connected with two sets of edges, one for each genome.

Additionally, by checking inversions on the found medians which do not change the median score, on average for each found median two more can be quickly located, though they are not significantly different from those already found. Table 7 shows the average number of medians found by our method. 4 Medians of Larger Genomes We tested the performance of our new method on some simulated datasets of larger genomes. The simulations were created with the same parameters, except the number of genes was increased to 500.

The direct optimization methods (GRAPPA and MGR) are based upon minimizing the number of inversion events, which requires either the false assumption that there is only one optimal median solution for a given problem instance, or the slightly weaker assumption that although multiple optimal solutions exist, they are all equally valuable for construction of trees. The issue is most evident when viewing the distances between found medians and the true ancestor: although it is still proportional to median score, increasing the number of events causes the optimal median and ancestor genome to diverge.

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