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Exact Multiple Sequence Alignment by Synchronized Decision Diagrams

机译:通过同步判定图来精确多个序列对齐

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This paper develops an exact solution algorithm for the multiple sequence alignment (MSA) problem. In the first step, we design a dynamic programming model and use it to construct a novel multivalued decision diagram (MDD) representation of all pairwise sequence alignments (PSA). PSA MDDs are then synchronized using side constraints to model the MSA problem as a mixed-integer program (MIP), for the first time, in polynomial space complexity. Two bound-based filtering procedures are developed to reduce the size of the MDDs, and the resulting MIP is solved using logic-based Benders decomposition. For a more effective algorithm, we develop a two-phase solution approach. In the first phase, we use optimistic filtering to quickly obtain a near-optimal bound, which we then use for exact filtering in the second phase to prove or obtain an optimal solution. Numerical results on benchmark instances show that our algorithm solves several instances to optimality for the first time, and, in case optimality cannot be proven, considerably improves upon a state-of-the-art heuristic MSA solver. Comparison with an existing state-of-the-art exact MSA algorithm shows that our approach is more time efficient and yields significantly smaller optimality gaps.
机译:本文开发用于多序列比对(MSA)问题的精确解算法。在第一个步骤中,我们设计了一个动态规划模型,并使用它来构造所有成对序列比对(PSA)的一种新颖的多值判决图(MDD)表示。 PSA MDDS然后使用方面的限制,建模的MSA的问题,因为混合整数规划(MIP),首次在多项式空间复杂度同步。两个结合为基础的过滤程序的开发,以减少MDDS的大小,并将所得MIP使用的基于逻辑的折弯机分解解决。为了更有效的算法,我们开发了一个两阶段解决方案的方法。在第一阶段中,我们使用乐观滤波来迅速地获得接近最佳的结合,这是我们然后用于精确过滤在第二阶段,以证明或获得最优解。基准上的情况下,计算结果表明,我们的算法解决几个实例最优的第一次,并且,在最优的情况下不能被证明,大大提高了在一个国家的最先进的启发式MSA求解。比较与现有状态的最先进的确切MSA算法显示,我们的方法是更有效的时间和产量显著较小最优的间隙。

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