首页> 外文会议>International Colloquium on Automata, Languages and Programming(ICALP 2006); 20060710-14; Venice(IT) >Fixed Parameter Tractability of Binary Near-Perfect Phylogenetic Tree Reconstruction
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Fixed Parameter Tractability of Binary Near-Perfect Phylogenetic Tree Reconstruction

机译:二元近乎完美的进化树重建的固定参数可牵引性

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We consider the problem of finding a Steiner minimum tree in a hypercube. Specifically, given n terminal vertices in an m dimensional cube and a parameter q, we compute the Steiner minimum tree in time O(72~q + 8~qnm~2), under the assumption that the length of the minimum Steiner tree is at most m + q. This problem has extensive applications in taxonomy and biology. The Steiner tree problem in hypercubes is equivalent to the phylogeny (evolutionary tree) reconstruction problem under the maximum parsimony criterion, when each taxon is defined over binary states. The taxa, character set and mutation of a phylogeny correspond to terminal vertices, dimensions and traversal of a dimension in a Steiner tree. Phylogenetic trees that mutate each character exactly once are called perfect phylo-genies and their size is bounded by the number of characters. When a perfect phylogeny consistent with the data set exists it can be constructed in linear time. However, real data sets often do not admit perfect phylogenies. In this paper, we consider the problem of reconstructing near-perfect phylogenetic trees (referred to as BNPP). A near-perfect phylogeny relaxes the perfect phylogeny assumption by allowing at most q additional mutations. We show for the first time that the BNPP problem is fixed parameter tractable (FPT) and significantly improve the previous asymptotic bounds.
机译:我们考虑在超立方体中找到Steiner最小树的问题。具体来说,给定一个m维立方体中的n个终端顶点和一个参数q,我们在最小Steiner树长度为的情况下,计算时间为O(72〜q + 8〜qnm〜2)的Steiner最小树。最多m + q。这个问题在分类学和生物学中有广泛的应用。当每个分类单元都在二元状态上定义时,超立方体中的Steiner树问题等同于最大简约准则下的系统发生(进化树)重构问题。系统分类的分类单元,字符集和突变对应于Steiner树中的最终顶点,维度和维度的遍历。将每个字符精确变异一次的系统发育树称为完美系统进化树,其大小受字符数限制。当存在与数据集一致的完美系统发育时,可以在线性时间内构建它。但是,真实的数据集通常不允许完美的系统发育。在本文中,我们考虑了重建近乎完美的系统发育树(称为BNPP)的问题。近乎完美的系统发育通过允许最多q个其他突变放松了完美的系统发育假设。我们首次证明BNPP问题是固定参数易处理的(FPT),并且显着改善了以前的渐近边界。

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