4 Search Results for "Lonardi, Stefano"

Document
DOI: 10.4230/LIPIcs.CPM.2025.18
Improved Circular Dictionary Matching

Authors: Nicola Cotumaccio

Published in: LIPIcs, Volume 331, 36th Annual Symposium on Combinatorial Pattern Matching (CPM 2025)

Abstract
The circular dictionary matching problem is an extension of the classical dictionary matching problem where every string in the dictionary is interpreted as a circular string: after reading the last character of a string, we can move back to its first character. The circular dictionary matching problem is motivated by applications in bioinformatics and computational geometry. In 2011, Hon et al. [ISAAC 2011] showed how to efficiently solve circular dictionary matching queries within compressed space by building on Mantaci et al.’s eBWT and Sadakane’s compressed suffix tree. The proposed solution is based on the assumption that the strings in the dictionary are all distinct and non-periodic, no string is a circular rotation of some other string, and the strings in the dictionary have similar lengths. In this paper, we consider arbitrary dictionaries, and we show how to solve circular dictionary matching queries in O((m + occ) log n) time within compressed space using n log σ (1 + o(1)) + O(n) + O(d log n) bits, where n is the total length of the dictionary, m is the length of the pattern, occ is the number of occurrences, d is the number of strings in the dictionary and σ is the size of the alphabet. Our solution is based on an extension of the suffix array to arbitrary dictionaries and a sampling mechanism for the LCP array of a dictionary inspired by recent results in graph indexing and compression.
Cite as

Nicola Cotumaccio. Improved Circular Dictionary Matching. In 36th Annual Symposium on Combinatorial Pattern Matching (CPM 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 331, pp. 18:1-18:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{cotumaccio:LIPIcs.CPM.2025.18,
  author =	{Cotumaccio, Nicola},
  title =	{{Improved Circular Dictionary Matching}},
  booktitle =	{36th Annual Symposium on Combinatorial Pattern Matching (CPM 2025)},
  pages =	{18:1--18:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-369-0},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{331},
  editor =	{Bonizzoni, Paola and M\"{a}kinen, Veli},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2025.18},
  URN =		{urn:nbn:de:0030-drops-231122},
  doi =		{10.4230/LIPIcs.CPM.2025.18},
  annote =	{Keywords: Circular pattern matching, dictionary matching, suffix tree, compressed suffix tree, suffix array, LCP array, Burrows-Wheeler Transform, FM-index}
}
Document
DOI: 10.4230/LIPIcs.CPM.2025.28
Faster Approximate Elastic-Degenerate String Matching - Part A

Authors: Solon P. Pissis, Jakub Radoszewski, and Wiktor Zuba

Published in: LIPIcs, Volume 331, 36th Annual Symposium on Combinatorial Pattern Matching (CPM 2025)

Abstract
An elastic-degenerate (ED) string 𝐓 is a sequence 𝐓 = 𝐓[1] ⋯ 𝐓[n] of n finite sets of strings. The cardinality m of 𝐓 is the total number of strings in 𝐓[i], for all i ∈ [1..n]. The size N of 𝐓 is the total length of all m strings of 𝐓. ED strings have been introduced to represent a set of closely-related DNA sequences. Let P = P[1..p] be a pattern of length p and k > 0 be an integer. We consider the problem of k-Approximate ED String Matching (EDSM): searching k-approximate occurrences of P in the language of 𝐓. We call k-Approximate EDSM under the Hamming distance, k-Mismatch EDSM; and we call k-Approximate EDSM under edit distance, k-Edit EDSM. Bernardini et al. (Theoretical Computer Science, 2020) showed a simple 𝒪(k m p + kN)-time algorithm for k-Mismatch EDSM and an 𝒪(k² m p + kN)-time algorithm for k-Edit EDSM. We improve the dependency on k in both results, obtaining an Õ(k^{2/3}mp+√kN)-time algorithm for k-Mismatch EDSM and an Õ(kmp+ kN)-time algorithm for k-Edit EDSM. Bernardini et al. (Theory of Computing Systems, 2024) presented several algorithms for 1-Approximate EDSM working in Õ(np²+N) time. They have also left the possibility to generalize these solutions for k > 1 as an open problem. We improve the runtime of their solution for 1-Mismatch and 1-Edit EDSM from Õ(np²+N) to 𝒪(np²+N). We further show algorithms for k-Approximate EDSM for the Hamming and edit distances working in Õ(np² + N) time, for any constant k > 0. Finally, we show how our techniques can be applied to improve upon the complexity of the k-Approximate ED String Intersection and k-Approximate Doubly EDSM problems that were introduced very recently by Gabory et al. (Information and Computation, 2025).
Cite as

Solon P. Pissis, Jakub Radoszewski, and Wiktor Zuba. Faster Approximate Elastic-Degenerate String Matching - Part A. In 36th Annual Symposium on Combinatorial Pattern Matching (CPM 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 331, pp. 28:1-28:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{pissis_et_al:LIPIcs.CPM.2025.28,
  author =	{Pissis, Solon P. and Radoszewski, Jakub and Zuba, Wiktor},
  title =	{{Faster Approximate Elastic-Degenerate String Matching - Part A}},
  booktitle =	{36th Annual Symposium on Combinatorial Pattern Matching (CPM 2025)},
  pages =	{28:1--28:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-369-0},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{331},
  editor =	{Bonizzoni, Paola and M\"{a}kinen, Veli},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2025.28},
  URN =		{urn:nbn:de:0030-drops-231227},
  doi =		{10.4230/LIPIcs.CPM.2025.28},
  annote =	{Keywords: ED string, approximate string matching, Hamming distance, edit distance}
}
Document
DOI: 10.4230/LIPIcs.WABI.2017.19
ThIEF: Finding Genome-wide Trajectories of Epigenetics Marks

Authors: Anton Polishko, Md. Abid Hasan, Weihua Pan, Evelien M. Bunnik, Karine Le Roch, and Stefano Lonardi

Published in: LIPIcs, Volume 88, 17th International Workshop on Algorithms in Bioinformatics (WABI 2017)

Abstract
We address the problem of comparing multiple genome-wide maps representing nucleosome positions or specific histone marks. These maps can originate from the comparative analysis of ChIP-Seq/MNase-Seq/FAIRE-Seq data for different cell types/tissues or multiple time points. The input to the problem is a set of maps, each of which is a list of genomics locations for nucleosomes or histone marks. The output is an alignment of nucleosomes/histone marks across time points (that we call trajectories), allowing small movements and gaps in some of the maps. We present a tool called ThIEF (TrackIng of Epigenetic Features) that can efficiently compute these trajectories. ThIEF comes into two "flavors": ThIEF:Iterative finds the trajectories progressively using bipartite matching, while ThIEF:LP solves a k-partite matching problem on a hyper graph using linear programming. ThIEF:LP is guaranteed to find the optimal solution, but it is slower than ThIEF:Iterative. We demonstrate the utility of ThIEF by providing an example of applications on the analysis of temporal nucleosome maps for the human malaria parasite. As a surprisingly remarkable result, we show that the output of ThIEF can be used to produce a supervised classifier that can accurately predict the position of stable nucleosomes (i.e., nucleosomes present in all time points) and unstable nucleosomes (i.e., present in at most half of the time points) from the primary DNA sequence. To the best of our knowledge, this is the first result on the prediction of the dynamics of nucleosomes solely based on their DNA binding preference. Software is available at https://github.com/ucrbioinfo/ThIEF.
Cite as

Anton Polishko, Md. Abid Hasan, Weihua Pan, Evelien M. Bunnik, Karine Le Roch, and Stefano Lonardi. ThIEF: Finding Genome-wide Trajectories of Epigenetics Marks. In 17th International Workshop on Algorithms in Bioinformatics (WABI 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 88, pp. 19:1-19:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{polishko_et_al:LIPIcs.WABI.2017.19,
  author =	{Polishko, Anton and Hasan, Md. Abid and Pan, Weihua and Bunnik, Evelien M. and Le Roch, Karine and Lonardi, Stefano},
  title =	{{ThIEF: Finding Genome-wide Trajectories of Epigenetics Marks}},
  booktitle =	{17th International Workshop on Algorithms in Bioinformatics (WABI 2017)},
  pages =	{19:1--19:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-050-7},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{88},
  editor =	{Schwartz, Russell and Reinert, Knut},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2017.19},
  URN =		{urn:nbn:de:0030-drops-76375},
  doi =		{10.4230/LIPIcs.WABI.2017.19},
  annote =	{Keywords: Nucleosomes, Histone Marks, Histone Tail Modifications, Epigenetics, Genomics}
}
Document
DOI: 10.4230/LIPIcs.WABI.2017.22
Efficient and Accurate Detection of Topologically Associating Domains from Contact Maps

Authors: Abbas Roayaei Ardakany and Stefano Lonardi

Published in: LIPIcs, Volume 88, 17th International Workshop on Algorithms in Bioinformatics (WABI 2017)

Abstract
Continuous improvements to high-throughput conformation capture (Hi-C) are revealing richerinformation about the spatial organization of the chromatin and its role in cellular functions.Several studies have confirmed the existence of structural features of the genome 3D organiza-tion that are stable across cell types and conserved across species, calledtopological associatingdomains(TADs). The detection of TADs has become a critical step in the analysis of Hi-C data,e.g., to identify enhancer-promoter associations. Here we presentEast, a novel TAD identifi-cation algorithm based on fast 2D convolution of Haar-like features, that is as accurate as thestate-of-the-art method based on the directionality index, but 75-80x faster.Eastis availablein the public domain at https://github.com/ucrbioinfo/EAST.
Cite as

Abbas Roayaei Ardakany and Stefano Lonardi. Efficient and Accurate Detection of Topologically Associating Domains from Contact Maps. In 17th International Workshop on Algorithms in Bioinformatics (WABI 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 88, pp. 22:1-22:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{roayaeiardakany_et_al:LIPIcs.WABI.2017.22,
  author =	{Roayaei Ardakany, Abbas and Lonardi, Stefano},
  title =	{{Efficient and Accurate Detection of Topologically Associating Domains from Contact Maps}},
  booktitle =	{17th International Workshop on Algorithms in Bioinformatics (WABI 2017)},
  pages =	{22:1--22:11},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-050-7},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{88},
  editor =	{Schwartz, Russell and Reinert, Knut},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2017.22},
  URN =		{urn:nbn:de:0030-drops-76446},
  doi =		{10.4230/LIPIcs.WABI.2017.22},
  annote =	{Keywords: Chromatin, TADs, 3D genome, Hi-C, contact maps}
}
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