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Ultrametric networks: a new tool for phylogenetic analysis

机译:超尺寸网络:系统发育分析的新工具

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Background The large majority of optimization problems related to the inference of distance‐based trees used in phylogenetic analysis and classification is known to be intractable. One noted exception is found within the realm of ultrametric distances. The introduction of ultrametric trees in phylogeny was inspired by a model of evolution driven by the postulate of a molecular clock, now dismissed, whereby phylogeny could be represented by a weighted tree in which the sum of the weights of the edges separating any given leaf from the root is the same for all leaves. Both, molecular clocks and rooted ultrametric trees, fell out of fashion as credible representations of evolutionary change. At the same time, ultrametric dendrograms have shown good potential for purposes of classification in so far as they have proven to provide good approximations for additive trees. Most of these approximations are still intractable, but the problem of finding the nearest ultrametric distance matrix to a given distance matrix with respect to the L distance has been long known to be solvable in polynomial time, the solution being incarnated in any minimum spanning tree for the weighted graph subtending to the matrix. Results This paper expands this subdominant ultrametric perspective by studying ultrametric networks, consisting of the collection of all edges involved in some minimum spanning tree. It is shown that, for a graph with n vertices, the construction of such a network can be carried out by a simple algorithm in optimal time O(n2) which is faster by a factor of n than the direct adaptation of the classical O(n3) paradigm by Warshall for computing the transitive closure of a graph. This algorithm, called UltraNet, will be shown to be easily adapted to compute relaxed networks and to support the introduction of artificial points to reduce the maximum distance between vertices in a pair. Finally, a few experiments will be discussed to demonstrate the applicability of subdominant ultrametric networks. Availability http://www.dei.unipd.it/~ciompin/main/Ultranet/Ultranet.html webcite
机译:背景技术绝大多数与系统树分析和分类中基于距离的树的推理有关的优化问题是众所周知的。在超测距领域中发现了一个值得注意的例外。超分子树在系统发育中的引入是受分子钟的假设驱动的进化模型的启发,该模型现已被废除,其中系统发育可以由加权树表示,其中将任何给定叶片与所有叶子的根都相同。分子钟和根深蒂固的树都已不合时宜地成为进化变化的可靠代表。同时,超量级树状图显示出良好的潜力,可用于分类,但已证明它们可以为加法树提供良好的近似值。这些近似中的大多数仍然是棘手的,但是早就知道在多项式时间内可以解决相对于L 距离最接近给定距离矩阵的超测距离矩阵的问题。可以在任何最小生成树中包含在矩阵中的加权图。结果本文通过研究超测量网络扩展了这种超主流的超测量视角,超网络包括一些最小生成树中所有边的集合。结果表明,对于具有n个顶点的图,可以通过一种简单的算法在最短时间O(n 2 )中实现这种网络的构建,该时间快n倍,比Warshall对经典O(n 3 )范例的直接适应,用于计算图的传递闭合。这种称为UltraNet的算法将被证明很容易用于计算松弛网络并支持引入人工点以减少一对顶点之间的最大距离。最后,将讨论一些实验以证明主要的超度量网络的适用性。可用性http://www.dei.unipd.it/~ciompin/main/Ultranet/Ultranet.html网站

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