On Stabbing Queries for Generalized Longest Repeat
November 07, 2015 Β· Declared Dead Β· π IEEE International Conference on Bioinformatics and Biomedicine
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Bojian Xu
arXiv ID
1511.02393
Category
cs.DS: Data Structures & Algorithms
Citations
2
Venue
IEEE International Conference on Bioinformatics and Biomedicine
Last Checked
4 months ago
Abstract
A longest repeat query on a string, motivated by its applications in many subfields including computational biology, asks for the longest repetitive substring(s) covering a particular string position (point query). In this paper, we extend the longest repeat query from point query to \emph{interval query}, allowing the search for longest repeat(s) covering any position interval, and thus significantly improve the usability of the solution. Our method for interval query takes a different approach using the insight from a recent work on \emph{shortest unique substrings} [1], as the prior work's approach for point query becomes infeasible in the setting of interval query. Using the critical insight from [1], we propose an indexing structure, which can be constructed in the optimal $O(n)$ time and space for a string of size $n$, such that any future interval query can be answered in $O(1)$ time. Further, our solution can find \emph{all} longest repeats covering any given interval using optimal $O(occ)$ time, where $occ$ is the number of longest repeats covering that given interval, whereas the prior $O(n)$-time and space work can find only one candidate for each point query. Experiments with real-world biological data show that our proposal is competitive with prior works, both time and space wise, while providing with the new functionality of interval queries as opposed to point queries provided by prior works.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Data Structures & Algorithms
π
π
The Cartographer
R.I.P.
π»
Ghosted
Route Planning in Transportation Networks
R.I.P.
π»
Ghosted
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
R.I.P.
π»
Ghosted
Hierarchical Clustering: Objective Functions and Algorithms
R.I.P.
π»
Ghosted
Graph Isomorphism in Quasipolynomial Time
π
π
The Cartographer
Simulation optimization: A review of algorithms and applications
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted