提出新方法解决序列比对中的可变间隔最长公共子序列问题。
On Solving the Multiple Variable Gapped Longest Common Subsequence Problem

- 基于根状状态图的搜索框架,动态维护候选节点池
- 在320个合成实例上实现比基线方法更优的稳定性
- 适合生物序列分析与时间序列事件匹配场景
本文研究可变间隔最长公共子序列(VGLCS)问题,该问题是经典最长公共子序列(LCS)问题的扩展,允许字符间存在灵活的间隔约束。该问题在分子序列比对中用于保持残基间的结构距离,在时间序列分析中则用于约束事件发生的时序延迟。我们提出一种基于根状状态图表示的搜索框架,其状态空间由大量根状子图构成。为应对组合爆炸,采用迭代束搜索策略,动态维护全局候选根节点池,有效控制迭代间的多样性。同时,将传统LCS文献中的若干启发式方法融入独立束搜索过程。据我们所知,这是首个针对VGLCS问题的全面计算研究,包含最多10条输入序列、每条序列最多500字符的320个合成实例。实验表明,所提方法在相近运行时间内优于基线束搜索,表现出更强鲁棒性。
原文摘要 · Abstract (English)
This paper addresses the Variable Gapped Longest Common Subsequence (VGLCS) problem, a generalization of the classical LCS problem involving flexible gap constraints between consecutive solutions' characters. The problem arises in molecular sequence comparison, where structural distance constraints between residues must be respected, and in time-series analysis where events are required to occur within specified temporal delays. We propose a search framework based on the root-based state graph representation, in which the state space comprises a generally large number of rooted state subgraphs. To cope with the resulting combinatorial explosion, an iterative beam search strategy is employed, dynamically maintaining a global pool of promising candidate root nodes, enabling effective control of diversification across iterations. To exploit the search for high-quality solutions, several known heuristics from the LCS literature are utilized into the standalone beam search procedure. To the best of our knowledge, this is the first comprehensive computational study on the VGLCS problem comprising 320 synthetic instances with up to 10 input sequences and up to 500 characters. Experimental results show robustness of the designed approach over the baseline beam search in comparable runtimes.
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