Titlebook: Comparative Genomics; International Worksh Francesca D. Ciccarelli,István Miklós Conference proceedings 2009 Springer-Verlag Berlin Heidelb

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书目名称Comparative Genomics影响因子(影响力)




书目名称Comparative Genomics影响因子(影响力)学科排名




书目名称Comparative Genomics网络公开度




书目名称Comparative Genomics网络公开度学科排名




书目名称Comparative Genomics被引频次




书目名称Comparative Genomics被引频次学科排名




书目名称Comparative Genomics年度引用




书目名称Comparative Genomics年度引用学科排名




书目名称Comparative Genomics读者反馈




书目名称Comparative Genomics读者反馈学科排名

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Parking Functions, Labeled Trees and DCJ Sorting Scenarios, This problem is related to the uniform generation of rearrangement scenarios, and the derivation of tests of statistical significance of the properties of these scenarios. Here we give an exact formula for the number of double-cut-and-join (DCJ) rearrangement scenarios of co-tailed genomes. We also

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Minimal Conflicting Sets for the Consecutive Ones Property in Ancestral Genome Reconstruction, set of rows that does not have the C1P, but every proper subset has the C1P. Such submatrices have been considered in comparative genomics applications, but very little is known about their combinatorial structure and efficient algorithms to compute them. We first describe an algorithm that detects

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Finding Nested Common Intervals Efficiently,as permutations or as sequences. Considering permutations, we give several algorithms whose running time depends on the size of the actual output rather than the output in the worst case. Indeed, we first provide a straightforward .(..) time algorithm for finding all nested common intervals. We redu

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Rearrangement Models and Single-Cut Operations,precisely defined, the general notion of a model remains undefined. In this paper, we give a formal set-theoretic definition, which allows us to investigate and prove relationships between distances under various existing and new models. We also initiate the formal study of single-cut operations by

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Inferring the Recent Duplication History of a Gene Cluster,ract evolutionary information from sequence data for such clusters are currently imperfect, in part because accurate sequence data are often lacking in these genomic regions, making the existing methods difficult to apply. We describe a new method for reconstructing the recent evolutionary history o