Algorithms in Bioinformatics: 8th International Workshop, by Eric Tannier, Chunfang Zheng, David Sankoff (auth.), Keith

By Eric Tannier, Chunfang Zheng, David Sankoff (auth.), Keith A. Crandall, Jens Lagergren (eds.)

This e-book constitutes the refereed complaints of the eighth foreign Workshop on Algorithms in Bioinformatics, WABI 2008, held in Karlsruhe, Germany, in September 2008 as a part of the ALGO 2008 meeting.

The 32 revised complete papers awarded including the summary of a keynote speak have been rigorously reviewed and chosen from eighty one submissions. All present problems with algorithms in bioinformatics are addressed, achieving from mathematical instruments to experimental experiences of approximation algorithms and reviews on major computational analyses. the subjects diversity in organic applicability from genome mapping, to series meeting, to microarray caliber, to phylogenetic inference, to molecular modeling.

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Extra resources for Algorithms in Bioinformatics: 8th International Workshop, WABI 2008, Karlsruhe, Germany, September 15-19, 2008. Proceedings

Example text

If there is no such solution, no genome exists whose sum of HP distances between it and the input genomes is better than T + 1. We increase the target value by 1 and start the algorithm again. Though some non-optimal solutions can pass the lower bound test, they can not pass the HP distance test. But any optimal genome that passes the lower bound test will also pass the HP distance test according to Theorem 1. The first optimal genome (there may be several) encountered will be outputted as the optimal RMP solution.

Our extensive experiments show that this method is more accurate than existing methods. However, this method is still primitive needs further improvements. In recent years, the double-cut-and-join (DCJ) distance has attracted much attention. We find that the lower bound 24 M. Zhang, W. Arndt, and J. Tang used in this paper is indeed very similar to the DCJ distance [2], thus it may be relatively easy to extend our work and develop a new DCJ median solver. Acknowledgments WA and JT are supported by US National Institutes of Health (NIH grant number R01 GM078991-01).

A. Crandall and J. ): WABI 2008, LNBI 5251, pp. 25–37, 2008. W. Xu and D. Sankoff Fig. 1. Left: unrooted phylogeny with open dots representing ancestral genomes to be inferred. Middle: median problem with three given genomes g, h and k and median q to be inferred. Right: decomposition of phylogeny into overlapping median problems. reversals and translocations in genomic distance calculations, within a framework known as “double cut and join” (DCJ). Moreover, the DCJ framework allows for substantial mathematical simplification of the distance calculation.

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