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Convex Recolorings of Strings and Trees: Definitions, Hardness Results and Algorithms

机译:横向和树木的凸起重新吸罗:定义,硬度结果和算法

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A coloring of a tree is convex if the vertices that pertain to any color induce a connected subtree. Convex colorings of trees arise in areas such as phylogenetics, linguistics, etc. e.g., a perfect phylogenetic tree is one in which the states of each character induce a convex coloring of the tree. When a coloring of a tree is not convex, it is desirable to know "how far" it is from a convex one, and what are the convex colorings which are "closest" to it. In this paper we study a natural definition of this distance - the recoloring distance, which is the minimal number of color changes at the vertices needed to make the coloring convex. We show that finding this distance is NP-hard even for a path, and for some other interesting variants of the problem. In the positive side, we present algorithms for computing the recoloring distance under some natural generalizations of this concept: the uniform weighted model and the non-uniform model. Our first algorithms find optimal convex recolorings of strings and bounded degree trees under the non-uniform model in linear time for any fixed number of colors. Next we improve these algorithms for the uniform model to run in linear time for any fixed number of bad colors. Finally, we generalize the above result to hold for trees of unbounded degree.
机译:如果与任何颜色有关的顶点诱导连接的子树,则树的着色是凸出的。树木的凸起着色在诸如系统发育,语言学等区域中的区域,例如,一个完美的系统发育树是每个角色的状态诱导树的凸起着色之一。当树的着色不是凸出的时,希望知道它是从凸起的一个“多远”,并且是什么是“最接近”的凸色。在本文中,我们研究了这种距离的自然定义 - 重新旋转距离,这是制作着色凸起所需的顶点的最小颜色变化数。我们表明,即使是一条路径,也可以找到这种距离是NP - 硬的问题,以及用于解决问题的其他一些有趣的变体。在正面,我们提供了在该概念的一些自然概括下计算重新定位距离的算法:均匀加权模型和非均匀模型。我们的第一算法在线性时间下找到了在非统一模型下的串和有界度树的最佳凸起折叠,以进行任何固定数量的颜色。接下来,我们改进了这些算法的统一模型,以在线性时间运行任何固定数量的坏颜色。最后,我们概括了上述结果,以保持无限程度的树木。

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