378 research outputs found

    Spotting Trees with Few Leaves

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    We show two results related to the Hamiltonicity and kk-Path algorithms in undirected graphs by Bj\"orklund [FOCS'10], and Bj\"orklund et al., [arXiv'10]. First, we demonstrate that the technique used can be generalized to finding some kk-vertex tree with ll leaves in an nn-vertex undirected graph in O(1.657k2l/2)O^*(1.657^k2^{l/2}) time. It can be applied as a subroutine to solve the kk-Internal Spanning Tree (kk-IST) problem in O(min(3.455k,1.946n))O^*(\min(3.455^k, 1.946^n)) time using polynomial space, improving upon previous algorithms for this problem. In particular, for the first time we break the natural barrier of O(2n)O^*(2^n). Second, we show that the iterated random bipartition employed by the algorithm can be improved whenever the host graph admits a vertex coloring with few colors; it can be an ordinary proper vertex coloring, a fractional vertex coloring, or a vector coloring. In effect, we show improved bounds for kk-Path and Hamiltonicity in any graph of maximum degree Δ=4,,12\Delta=4,\ldots,12 or with vector chromatic number at most 8

    Polynomial Kernels for Weighted Problems

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    Kernelization is a formalization of efficient preprocessing for NP-hard problems using the framework of parameterized complexity. Among open problems in kernelization it has been asked many times whether there are deterministic polynomial kernelizations for Subset Sum and Knapsack when parameterized by the number nn of items. We answer both questions affirmatively by using an algorithm for compressing numbers due to Frank and Tardos (Combinatorica 1987). This result had been first used by Marx and V\'egh (ICALP 2013) in the context of kernelization. We further illustrate its applicability by giving polynomial kernels also for weighted versions of several well-studied parameterized problems. Furthermore, when parameterized by the different item sizes we obtain a polynomial kernelization for Subset Sum and an exponential kernelization for Knapsack. Finally, we also obtain kernelization results for polynomial integer programs

    A strategy for the characterization of minute chromosome rearrangements using multiple color fluorescence in situ hybridization with chromosome-specific DNA libraries and YAC clones

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    The identification of marker chromosomes in clinical and tumor cytogenetics by chromosome banding analysis can create problems. In this study, we present a strategy to define minute chromosomal rearrangements by multicolor fluorescence in situ hybridization (FISH) with whole chromosome painting probes derived from chromosome-specific DNA libraries and Alu-polymerase chain reaction (PCR) products of various region-specific yeast artificial chromosome (YAC) clones. To demonstrate the usefulness of this strategy for the characterization of chromosome rearrangements unidentifiable by banding techniques, an 8p+ marker chromosome with two extra bands present in the karyotype of a child with multiple anomalies, malformations, and severe mental retardation was investigated. A series of seven-color FISH experiments with sets of fluorochrome-labeled DNA library probes from flow-sorted chromosomes demonstrated that the additional segment on 8p+ was derived from chromosome 6. For a more detailed characterization of the marker chromosome, three-color FISH experiments with library probes specific to chromosomes 6 and 8 were performed in combination with newly established telomeric and subtelomeric YAC clones from 6q25, 6p23, and 8p23. These experiments demonstrated a trisomy 6pter6p22 and a monosomy 8pter8p23 in the patient. The present limitations for a broad application of this strategy and its possible improvements are discusse
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