Computing and Combinatorics: 11th Annual International by Leslie G. Valiant (auth.), Lusheng Wang (eds.)

By Leslie G. Valiant (auth.), Lusheng Wang (eds.)

The refereed complaints of the eleventh Annual foreign Computing and Combinatorics convention, COCOON 2005, held in Kunming, China in August 2005.

The ninety six revised complete papers provided including abstracts of three invited talks have been conscientiously reviewed and chosen from 353 submissions. The papers disguise such a lot elements of theoretical machine technological know-how and combinatorics regarding computing and are equipped in topical sections on bioinformatics, networks, string algorithms, scheduling, complexity, steiner bushes, graph drawing and format layout, quantum computing, randomized algorithms, geometry, codes, finance, facility position, graph idea, graph algorithms.

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5. G. A. Pevzner, and G. Tesler. Reconstructing the genomic architecture of ancestral mammals: lessons from human, mouse and rat genomes. , 14(4):507–516, 2004. 6. D. Bryant. The complexity of calculating exemplar distances. In D. Sankoff and J. Nadeau, editors, Comparative Genomics: Empirical and Analytical Approaches to Gene Order Dynamics, Map Alignment, and the Evolution of Gene Families, pages 207–212. Kluwer Acad. , 2000. 7. M. Garey and D. Johnson. Computers and Intractability: A Guide to the Theory of NP-Completeness.

Let G = g1 g2 . . gn and H = h1 h2 . . hm be two genomes on F . A gene matching M between G and H is a maximal matching between genes of G and H such that, for every pair (gi , hj ) ∈ M, gi and hj belong to the same family. By maximal matching, we mean that for any gene family f , it is forbidden to have at the same time an occurrence of f in G and one in H that do not belong to M. It follows from the maximality condition of matchings that in any matching M between balanced genomes G and H, every gene of G is matched to a gene of H and conversely.

The number of longest common subsequences can be quite large. Greenberg [9] proved an exponential lower bound for the maximum number of distinct longest common subsequences of two sequences of length n. Therefore, in a lot of biological applications we believe that merely finding a longest common subsequence is not quite meaningful. In fact, finding a longest common subsequence satisfying a useful property is the goal of this paper. To the best of our knowledge, this has never done before, though there have been a lot of related work on identifying a (sub)string which is close to a set of given strings [13, 14] and close to a set of ‘bad’ strings and far from a set of ‘good’ strings [5].

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