On the String Matching with k Differences in DNA Databases
Yangjun Chen, Hoang Hai Nguyen
Abstract
In this paper, we discuss an efficient and effective index mechanism for the string matching with k differences, by which we will find all the substrings of a target string y of length n that align with a pattern string x of length m with not more than k insertions, deletions, and mismatches. A typical application is the searching of a DNA database, where the size of a genome sequence in the database is much larger than that of a pattern. For example, n is often on the order of millions or billions while m is just a hundred or a thousand. The main idea of our method is to transform y to a BWT-array as an index, denoted as BWT ( y ), and search x against it. The time complexity of our method is bounded by O( k · | T |), where T is a tree structure dynamically generated during a search of BWT ( y ). The average value of | T | is bounded by O(|Σ|
2 k
), where Σ is an alphabet from which we take symbols to make up target and pattern strings. This time complexity is better than previous strategies when k ≤ O(log |Σ| n ). The general working process consists of two steps. In the first step, x is decomposed into a series of l small subpatterns, and BWT ( y ) is utilized to speedup the process to figure out all the occurrences of such subpatterns with ⌊ k/l ⌋ differences. In the second step, all the found occurrences in the first step will be rechecked to see whether they really match x , but with k differences. Extensive experiments have been conducted, which show that our method for this problem is promising.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext c91e7104-40a9-4bd0-844c-da38964dab58Cited by top-tier papers1
Ask how each one uses itRelated papers
- Near-Optimal-Time Quantum Algorithms for Approximate Pattern MatchingTomasz Kociumaka, Jakob Nogler, Philip WellnitzSODA 2025 · 1 citation
- Faster two-dimensional pattern matching with k mismatchesJonas Ellert, Pawel Gawrychowski, Adam Górkiewicz, Tatiana StarikovskayaSODA 2025 · 1 citation
- Indexing Strings with UtilitiesGiulia Bernardini, Huiping Chen, Alessio Conte, Roberto Grossi et al.ICDE 2025
- Faster Approximate Pattern Matching: A Unified ApproachPanagiotis Charalampopoulos, Tomasz Kociumaka, Philip WellnitzFOCS 2020 · 2 citations
- FSMDTW: A Fast Index-free Subsequence Matching Algorithm for Dynamic Time WarpingZemin Chao, Qiaoyi Zheng, Zhixin Qi, Hongzhi WangVLDB 2025
