ArticleAlgorithms for molecular biology : AMB2014
Fast algorithms for approximate circular string matching.
Article in Algorithms for molecular biology : AMB, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Prediction of Circular RNA Secondary Structures and Their Targets.Advances in experimental medicine and biology · 2025Review
- Fast phylogenetic inference from typing data.Algorithms for molecular biology : AMB · 2018Article
- Article
- libFLASM: a software library for fixed-length approximate string matching.BMC bioinformatics · 2016Article
- Circular sequence comparison: algorithms and applications.Algorithms for molecular biology : AMB · 2016Article
- SimpLiFiCPM: A Simple and Lightweight Filter-Based Algorithm for Circular Pattern Matching.International journal of genomics · 2015Article
- Network analysis of circular permutations in multidomain proteins reveals functional linkages for uncharacterized proteins.Cancer informatics · 2014Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCircular string matching is a problem which naturally arises in many biological contexts. It consists in finding all occurrences of the rotations of a pattern of length m in a text of length n. There exist optimal average-case algorithms for exact circular string matching. Approximate circular string matching is a rather undeveloped area.
resultsIn this article, we present a suboptimal average-case algorithm for exact circular string matching requiring time O(n). Based on our solution for the exact case, we present two fast average-case algorithms for approximate circular string matching with k-mismatches, under the Hamming distance model, requiring time O(n) for moderate values of k, that is k=O(m/logm). We show how the same results can be easily obtained under the edit distance model. The presented algorithms are also implemented as library functions. Experimental results demonstrate that the functions provided in this library accelerate the computations by more than three orders of magnitude compared to a naïve approach.
conclusionsWe present two fast average-case algorithms for approximate circular string matching with k-mismatches; and show that they also perform very well in practice. The importance of our contribution is underlined by the fact that the provided functions may be seamlessly integrated into any biological pipeline. The source code of the library is freely available at http://www.inf.kcl.ac.uk/research/projects/asmf/.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.