9 Search Results for "Ziv-Ukelson, Michal"

Document
DOI: 10.4230/LIPIcs.ESA.2025.74
Core-Sparse Monge Matrix Multiplication: Improved Algorithm and Applications

Authors: Paweł Gawrychowski, Egor Gorbachev, and Tomasz Kociumaka

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract
Min-plus matrix multiplication is a fundamental tool for designing algorithms operating on distances in graphs and different problems solvable by dynamic programming. We know that, assuming the APSP hypothesis, no subcubic-time algorithm exists for the case of general matrices. However, in many applications the matrices admit certain structural properties that can be used to design faster algorithms. For example, when considering a planar graph, one often works with a Monge matrix A, meaning that the density matrix A^◻ has non-negative entries, that is, A^◻_{i,j} := A_{i+1,j} + A_{i,j+1} - A_{i,j} -A_{i+1,j+1} ≥ 0. The min-plus product of two n×n Monge matrices can be computed in 𝒪(n²) time using the famous SMAWK algorithm. In applications such as longest common subsequence, edit distance, and longest increasing subsequence, the matrices are even more structured, as observed by Tiskin [J. Discrete Algorithms, 2008]: they are (or can be converted to) simple unit-Monge matrices, meaning that the density matrix is a permutation matrix and, furthermore, the first column and the last row of the matrix consist of only zeroes. Such matrices admit an implicit representation of size 𝒪(n) and, as shown by Tiskin [SODA 2010 & Algorithmica, 2015], their min-plus product can be computed in 𝒪(nlog n) time. Russo [SPIRE 2010 & Theor. Comput. Sci., 2012] identified a general structural property of matrices that admit such efficient representation and min-plus multiplication algorithms: the core size δ, defined as the number of non-zero entries in the density matrices of the input and output matrices. He provided an adaptive implementation of the SMAWK algorithm that runs in 𝒪((n+δ)log³ n) or 𝒪((n+δ)log² n) time (depending on the representation of the input matrices). In this work, we further investigate the core size as the parameter that enables efficient min-plus matrix multiplication. On the combinatorial side, we provide a (linear) bound on the core size of the product matrix in terms of the core sizes of the input matrices. On the algorithmic side, we generalize Tiskin’s algorithm (but, arguably, with a more elementary analysis) to solve the core-sparse Monge matrix multiplication problem in 𝒪(n+δlog δ) ⊆ 𝒪(n + δ log n) time, matching the complexity for simple unit-Monge matrices. As witnessed by the recent work of Gorbachev and Kociumaka [STOC'25] for edit distance with integer weights, our generalization opens up the possibility of speed-ups for weighted sequence alignment problems. Furthermore, our multiplication algorithm is also capable of producing an efficient data structure for recovering the witness for any given entry of the output matrix. This allows us, for example, to preprocess an integer array of size n in Õ(n) time so that the longest increasing subsequence of any sub-array can be reconstructed in Õ(𝓁) time, where 𝓁 is the length of the reported subsequence. In comparison, Karthik C. S. and Rahul [arXiv, 2024] recently achieved 𝒪(𝓁+n^{1/2}polylog n)-time reporting after 𝒪(n^{3/2}polylog n)-time preprocessing.
Cite as

Paweł Gawrychowski, Egor Gorbachev, and Tomasz Kociumaka. Core-Sparse Monge Matrix Multiplication: Improved Algorithm and Applications. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 74:1-74:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{gawrychowski_et_al:LIPIcs.ESA.2025.74,
  author =	{Gawrychowski, Pawe{\l} and Gorbachev, Egor and Kociumaka, Tomasz},
  title =	{{Core-Sparse Monge Matrix Multiplication: Improved Algorithm and Applications}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{74:1--74:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.74},
  URN =		{urn:nbn:de:0030-drops-245427},
  doi =		{10.4230/LIPIcs.ESA.2025.74},
  annote =	{Keywords: Min-plus matrix multiplication, Monge matrix, longest increasing subsequence}
}
Document
DOI: 10.4230/LIPIcs.WABI.2025.21
Linear-Space Subquadratic-Time String Alignment Algorithm for Arbitrary Scoring Matrices

Authors: Ryosuke Yamano and Tetsuo Shibuya

Published in: LIPIcs, Volume 344, 25th International Conference on Algorithms for Bioinformatics (WABI 2025)

Abstract
Theoretically, the fastest algorithm by Crochemore et al. for computing the alignment of two given strings of size n over a constant alphabet takes O(n²/log n) time. The algorithm uses Lempel–Ziv parsing to divide the dynamic programming matrix into blocks and utilizes the repetitive structure. It is the only previously known subquadratic-time algorithm that can handle scoring matrices of arbitrary weights. However, this algorithm takes O(n²/log n) space, and reducing the space while preserving the time complexity has been an open problem for more than 20 years. We present a solution to this issue by achieving an O(n) space algorithm that maintains O(n²/log n) time. The classical refinement by Hirschberg reduces the space complexity of the textbook O(n²) algorithm to O(n) while preserving the quadratic time. However, applying this technique to the algorithm of Crochemore et al. has been considered challenging because their method requires O(n² / log n) space even when computing only the alignment score. Our modification enables the application of Hirschberg’s refinement, allowing traceback computation in O(n) space while preserving the O(n² / log n) overall time complexity. Our algorithm can be applied to both global and local string alignment problems.
Cite as

Ryosuke Yamano and Tetsuo Shibuya. Linear-Space Subquadratic-Time String Alignment Algorithm for Arbitrary Scoring Matrices. In 25th International Conference on Algorithms for Bioinformatics (WABI 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 344, pp. 21:1-21:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{yamano_et_al:LIPIcs.WABI.2025.21,
  author =	{Yamano, Ryosuke and Shibuya, Tetsuo},
  title =	{{Linear-Space Subquadratic-Time String Alignment Algorithm for Arbitrary Scoring Matrices}},
  booktitle =	{25th International Conference on Algorithms for Bioinformatics (WABI 2025)},
  pages =	{21:1--21:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-386-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{344},
  editor =	{Brejov\'{a}, Bro\v{n}a and Patro, Rob},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2025.21},
  URN =		{urn:nbn:de:0030-drops-239479},
  doi =		{10.4230/LIPIcs.WABI.2025.21},
  annote =	{Keywords: String alignment, dynamic programming, linear space algorithms}
}
Document
DOI: 10.4230/LIPIcs.WABI.2025.13
Spark: Sparsified Hierarchical Energy Minimization of RNA Pseudoknots

Authors: Mateo Gray, Sebastian Will, and Hosna Jabbari

Published in: LIPIcs, Volume 344, 25th International Conference on Algorithms for Bioinformatics (WABI 2025)

Abstract
Motivation. Determining RNA structure is essential for understanding RNA function and interaction networks. Although experimental techniques yield high‑accuracy structures, they are costly and time‑consuming; thus, computational approaches - especially minimum‑free‑energy (MFE) prediction algorithms - are indispensable. Accurately predicting pseudoknots, however, remains challenging because their inclusion usually leads to prohibitive computational complexity. Recent work demonstrated that sparsification can improve the efficiency of complex pseudoknot prediction algorithms such as Knotty. This finding suggests similar gains are possible for already efficient algorithms like HFold, which targets a complementary class of hierarchically constrained pseudoknots. Results. We introduce Spark, an exact, fully sparsified algorithm for predicting pseudoknotted RNA structures. Like its non‑sparsified predecessor HFold, Spark searches for the minimum‑energy structure under the HotKots 2.0 energy model, a pseudoknot extension of the Turner model. Because the sparsification is non‑heuristic, Spark preserves the asymptotic time‑ and space‑complexity guarantees of HFold while greatly reducing the constant factors. We benchmarked the performance of Spark against HFold and, as a pseudoknot‑free baseline, RNAfold. Compared with HFold, Spark substantially lowers both run time and memory usage, while achieving run‑time figures close to those of RNAfold. Across all tested sequence lengths, Spark used the least memory and consistently ran faster than HFold. Conclusion. By extending non‑heuristic sparsification to hierarchical pseudoknot prediction, Spark delivers an exceptionally fast and memory‑efficient tool accurate prediction of pseudoknotted RNA structures, enabling routine analysis of long sequences. The algorithm broadens the practical scope of computational RNA biology and provides a solid foundation for future advances in structure‑based functional annotation. Availability. Spark’s implementation and detailed results are available at https://github.com/TheCOBRALab/Spark.
Cite as

Mateo Gray, Sebastian Will, and Hosna Jabbari. Spark: Sparsified Hierarchical Energy Minimization of RNA Pseudoknots. In 25th International Conference on Algorithms for Bioinformatics (WABI 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 344, pp. 13:1-13:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{gray_et_al:LIPIcs.WABI.2025.13,
  author =	{Gray, Mateo and Will, Sebastian and Jabbari, Hosna},
  title =	{{Spark: Sparsified Hierarchical Energy Minimization of RNA Pseudoknots}},
  booktitle =	{25th International Conference on Algorithms for Bioinformatics (WABI 2025)},
  pages =	{13:1--13:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-386-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{344},
  editor =	{Brejov\'{a}, Bro\v{n}a and Patro, Rob},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2025.13},
  URN =		{urn:nbn:de:0030-drops-239383},
  doi =		{10.4230/LIPIcs.WABI.2025.13},
  annote =	{Keywords: RNA, MFE, Secondary Structure Prediction, Pseudoknot, Sparsification, Space Complexity, Time Complexity}
}
Document
Research
DOI: 10.4230/OASIcs.Grossi.18
DNA Is a Puzzle Enthusiast

Authors: Roberto Marangoni

Published in: OASIcs, Volume 132, From Strings to Graphs, and Back Again: A Festschrift for Roberto Grossi's 60th Birthday (2025)

Abstract
This article presents a concise summary of research projects in which Roberto Grossi participated, yielding interesting results that were never previously published in research papers. At the time, these studies were deemed too limited and in need of further extensions and generalizations, which were never realized due to a lack of resources. The researches focused on methods for inferring possible three-dimensional DNA conformations based on nucleotide sequence characteristics. Specifically, two key approaches were investigated: the identification of structured motifs for detecting Transcription Factor Binding Sites (TFBS) and the study of nested permutations using PQ-trees. This article describes the obtained results in selected case studies, their potential implications, and the current state of the art in these research areas.
Cite as

Roberto Marangoni. DNA Is a Puzzle Enthusiast. In From Strings to Graphs, and Back Again: A Festschrift for Roberto Grossi's 60th Birthday. Open Access Series in Informatics (OASIcs), Volume 132, pp. 18:1-18:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{marangoni:OASIcs.Grossi.18,
  author =	{Marangoni, Roberto},
  title =	{{DNA Is a Puzzle Enthusiast}},
  booktitle =	{From Strings to Graphs, and Back Again: A Festschrift for Roberto Grossi's 60th Birthday},
  pages =	{18:1--18:8},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-391-1},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{132},
  editor =	{Conte, Alessio and Marino, Andrea and Rosone, Giovanna and Vitter, Jeffrey Scott},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Grossi.18},
  URN =		{urn:nbn:de:0030-drops-238172},
  doi =		{10.4230/OASIcs.Grossi.18},
  annote =	{Keywords: DNA, 3D structure, PQ trees, structural motifs}
}
Document
DOI: 10.4230/LIPIcs.WABI.2022.11
New Algorithms for Structure Informed Genome Rearrangement

Authors: Eden Ozery, Meirav Zehavi, and Michal Ziv-Ukelson

Published in: LIPIcs, Volume 242, 22nd International Workshop on Algorithms in Bioinformatics (WABI 2022)

Abstract
We define two new computational problems in the domain of perfect genome rearrangements, and propose three algorithms to solve them. The rearrangement scenarios modeled by the problems consider Reversal and Block Interchange operations, and a PQ-tree is utilized to guide the allowed operations and to compute their weights. In the first problem, Constrained TreeToString Divergence (CTTSD), we define the basic structure-informed rearrangement based divergence measure. Here, we assume that the gene order members of the gene cluster from which the PQ-tree is constructed are permutations. The PQ-tree representing the gene cluster is ordered such that the series of gene IDs spelled by its leaves is equivalent to the reference gene order. Then, a structure-informed gene rearrangement measure is computed between the ordered PQ-tree and the target gene order. The second problem, TreeToString Divergence (TTSD), generalizes CTTSD, where the gene order members are not necessarily permutations and the structure-informed rearrangement based divergence measure is extended to also consider up to d_S and d_T gene insertion and deletion operations, respectively, when modelling the PQ-tree informed divergence process from the reference order to the target order. The first algorithm solves CTTSD in O(n γ² ⋅ (m_p ⋅ 1.381^γ + m_q)) time and O(n²) space, where γ is the maximum number of children of a node, n is the length of the string and the number of leaves in the tree, and m_p and m_q are the number of P-nodes and Q-nodes in the tree, respectively. If one of the penalties of CTTSD is 0, then the algorithm runs in O(n m γ²) time and O(n²) space. The second algorithm solves TTSD in O(n² γ² {d_T}² {d_S}² m² (m_p ⋅ 5^γ γ + m_q)) time and O(d_T d_S m (m n + 5^γ)) space, where γ is the maximum number of children of a node, n is the length of the string, m is the number of leaves in the tree, m_p and m_q are the number of P-nodes and Q-nodes in the tree, respectively, and allowing d_T deletions from the tree and d_S deletions from the string. The third algorithm is intended to reduce the space complexity of the second algorithm. It solves a variant of the problem (where one of the penalties of TTSD is 0) in O(n γ² {d_T}² {d_S}² m² (m_p ⋅ 4^γ γ²n(d_T+d_S+m+n) + m_q)) time and O(γ² n m² d_T d_S (d_T+d_S+m+n)) space. The algorithm is implemented as a software tool, denoted MEM-Rearrange, and applied to the comparative and evolutionary analysis of 59 chromosomal gene clusters extracted from a dataset of 1,487 prokaryotic genomes.
Cite as

Eden Ozery, Meirav Zehavi, and Michal Ziv-Ukelson. New Algorithms for Structure Informed Genome Rearrangement. In 22nd International Workshop on Algorithms in Bioinformatics (WABI 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 242, pp. 11:1-11:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{ozery_et_al:LIPIcs.WABI.2022.11,
  author =	{Ozery, Eden and Zehavi, Meirav and Ziv-Ukelson, Michal},
  title =	{{New Algorithms for Structure Informed Genome Rearrangement}},
  booktitle =	{22nd International Workshop on Algorithms in Bioinformatics (WABI 2022)},
  pages =	{11:1--11:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-243-3},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{242},
  editor =	{Boucher, Christina and Rahmann, Sven},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2022.11},
  URN =		{urn:nbn:de:0030-drops-170454},
  doi =		{10.4230/LIPIcs.WABI.2022.11},
  annote =	{Keywords: PQ-tree, Gene Cluster, Breakpoint Distance}
}
Document
DOI: 10.4230/LIPIcs.WABI.2020.1
Approximate Search for Known Gene Clusters in New Genomes Using PQ-Trees

Authors: Galia R. Zimerman, Dina Svetlitsky, Meirav Zehavi, and Michal Ziv-Ukelson

Published in: LIPIcs, Volume 172, 20th International Workshop on Algorithms in Bioinformatics (WABI 2020)

Abstract
We define a new problem in comparative genomics, denoted PQ-Tree Search, that takes as input a PQ-tree T representing the known gene orders of a gene cluster of interest, a gene-to-gene substitution scoring function h, integer parameters d_T and d_S, and a new genome S. The objective is to identify in S approximate new instances of the gene cluster that could vary from the known gene orders by genome rearrangements that are constrained by T, by gene substitutions that are governed by h, and by gene deletions and insertions that are bounded from above by d_T and d_S, respectively. We prove that the PQ-Tree Search problem is NP-hard and propose a parameterized algorithm that solves the optimization variant of PQ-Tree Search in O^*(2^{γ}) time, where γ is the maximum degree of a node in T and O^* is used to hide factors polynomial in the input size. The algorithm is implemented as a search tool, denoted PQFinder, and applied to search for instances of chromosomal gene clusters in plasmids, within a dataset of 1,487 prokaryotic genomes. We report on 29 chromosomal gene clusters that are rearranged in plasmids, where the rearrangements are guided by the corresponding PQ-tree. One of these results, coding for a heavy metal efflux pump, is further analysed to exemplify how PQFinder can be harnessed to reveal interesting new structural variants of known gene clusters.
Cite as

Galia R. Zimerman, Dina Svetlitsky, Meirav Zehavi, and Michal Ziv-Ukelson. Approximate Search for Known Gene Clusters in New Genomes Using PQ-Trees. In 20th International Workshop on Algorithms in Bioinformatics (WABI 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 172, pp. 1:1-1:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{zimerman_et_al:LIPIcs.WABI.2020.1,
  author =	{Zimerman, Galia R. and Svetlitsky, Dina and Zehavi, Meirav and Ziv-Ukelson, Michal},
  title =	{{Approximate Search for Known Gene Clusters in New Genomes Using PQ-Trees}},
  booktitle =	{20th International Workshop on Algorithms in Bioinformatics (WABI 2020)},
  pages =	{1:1--1:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-161-0},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{172},
  editor =	{Kingsford, Carl and Pisanti, Nadia},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2020.1},
  URN =		{urn:nbn:de:0030-drops-127906},
  doi =		{10.4230/LIPIcs.WABI.2020.1},
  annote =	{Keywords: PQ-Tree, Gene Cluster, Efflux Pump}
}
Document
DOI: 10.4230/LIPIcs.WABI.2019.9
A New Paradigm for Identifying Reconciliation-Scenario Altering Mutations Conferring Environmental Adaptation

Authors: Roni Zoller, Meirav Zehavi, and Michal Ziv-Ukelson

Published in: LIPIcs, Volume 143, 19th International Workshop on Algorithms in Bioinformatics (WABI 2019)

Abstract
An important goal in microbial computational genomics is to identify crucial events in the evolution of a gene that severely alter the duplication, loss and mobilization patterns of the gene within the genomes in which it disseminates. In this paper, we formalize this microbiological goal as a new pattern-matching problem in the domain of Gene tree and Species tree reconciliation, denoted "Reconciliation-Scenario Altering Mutation (RSAM) Discovery". We propose an O(m * n * k) time algorithm to solve this new problem, where m and n are the number of vertices of the input Gene tree and Species tree, respectively, and k is a user-specified parameter that bounds from above the number of optimal solutions of interest. The algorithm first constructs a hypergraph representing the k highest scoring reconciliation scenarios between the given Gene tree and Species tree, and then interrogates this hypergraph for subtrees matching a pre-specified RSAM Pattern. Our algorithm is optimal in the sense that the number of hypernodes in the hypergraph can be lower bounded by Omega(m * n * k). We implement the new algorithm as a tool, denoted RSAM-finder, and demonstrate its application to the identification of RSAMs in toxins and drug resistance elements across a dataset spanning hundreds of species.
Cite as

Roni Zoller, Meirav Zehavi, and Michal Ziv-Ukelson. A New Paradigm for Identifying Reconciliation-Scenario Altering Mutations Conferring Environmental Adaptation. In 19th International Workshop on Algorithms in Bioinformatics (WABI 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 143, pp. 9:1-9:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{zoller_et_al:LIPIcs.WABI.2019.9,
  author =	{Zoller, Roni and Zehavi, Meirav and Ziv-Ukelson, Michal},
  title =	{{A New Paradigm for Identifying Reconciliation-Scenario Altering Mutations Conferring Environmental Adaptation}},
  booktitle =	{19th International Workshop on Algorithms in Bioinformatics (WABI 2019)},
  pages =	{9:1--9:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-123-8},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{143},
  editor =	{Huber, Katharina T. and Gusfield, Dan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2019.9},
  URN =		{urn:nbn:de:0030-drops-110398},
  doi =		{10.4230/LIPIcs.WABI.2019.9},
  annote =	{Keywords: Gene tree, Species tree, Reconciliation}
}
Document
Invited Talk
DOI: 10.4230/LIPIcs.CPM.2019.3
Stringology Combats Microbiological Threats (Invited Talk)

Authors: Michal Ziv-Ukelson

Published in: LIPIcs, Volume 128, 30th Annual Symposium on Combinatorial Pattern Matching (CPM 2019)

Abstract
A major concern worldwide is the acquisition of antibiotic resistance by pathogenic bacteria. Genomic elements carrying resistance and virulence function can be acquired through horizontal gene transfer, yielding a broad spread of evolutionary successful elements, both within and in between species, with devastating effect. Recent advances in pyrosequencing techniques, combined with global efforts to study microbial adaptation to a wide range of ecological niches (and in particular to life in host tissues that we perceive as pathogenesis), yield huge and rapidly-growing databases of microbial genomes. This big new data statistically empowers genomic-context based approaches to functional analysis: the idea is that groups of genes that are clustered locally together across many genomes usually express protein products that interact in the same biological pathway, and thus the function of a new, uncharacterized gene can be deciphered based on the previously characterized genes that are co-localized with it in the same gene cluster. Identifying and interpreting microbial gene context in huge genomic data requires efficient string-based data mining algorithms. Additionally, new computational challenges are raised by the need to study the grammar and evolutionary spreading patterns of microbial gene context. In this talk, we will review some classical combinatorial pattern matching and data mining problems, previously inspired by this application domain. We will re-examine the biological assumptions behind the previously proposed models in light of some new biological observations. We will consider the computational challenges arising in accomodating the new biological observations, and in exploiting them to scale up the algorithmic solutions to the huge new data. Our goal is to inspire interesting new problems that harness Stringology to the study of microbial adaptation and to the fight against microbiological threats ...
Cite as

Michal Ziv-Ukelson. Stringology Combats Microbiological Threats (Invited Talk). In 30th Annual Symposium on Combinatorial Pattern Matching (CPM 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 128, p. 3:1, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{zivukelson:LIPIcs.CPM.2019.3,
  author =	{Ziv-Ukelson, Michal},
  title =	{{Stringology Combats Microbiological Threats}},
  booktitle =	{30th Annual Symposium on Combinatorial Pattern Matching (CPM 2019)},
  pages =	{3:1--3:1},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-103-0},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{128},
  editor =	{Pisanti, Nadia and P. Pissis, Solon},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2019.3},
  URN =		{urn:nbn:de:0030-drops-104748},
  doi =		{10.4230/LIPIcs.CPM.2019.3},
  annote =	{Keywords: comparative genomics, syntenic blocks, gene clusters, reconciliation of gene and species trees}
}
Document
DOI: 10.4230/LIPIcs.CPM.2016.17
On Almost Monge All Scores Matrices

Authors: Amir Carmel, Dekel Tsur, and Michal Ziv-Ukelson

Published in: LIPIcs, Volume 54, 27th Annual Symposium on Combinatorial Pattern Matching (CPM 2016)

Abstract
The all scores matrix of a grid graph is a matrix containing the optimal scores of paths from every vertex on the first row of the graph to every vertex on the last row. This matrix is commonly used to solve diverse string comparison problems. All scores matrices have the Monge property, and this was exploited by previous works that used all scores matrices for solving various problems. In this paper, we study an extension of grid graphs that contain an additional set of edges, called bridges. Our main result is to show several properties of the all scores matrices of such graphs. We also give an O(r(nm + n2)) time algorithm for constructing the all scores matrix of an m × n grid graph with r bridges.
Cite as

Amir Carmel, Dekel Tsur, and Michal Ziv-Ukelson. On Almost Monge All Scores Matrices. In 27th Annual Symposium on Combinatorial Pattern Matching (CPM 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 54, pp. 17:1-17:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@InProceedings{carmel_et_al:LIPIcs.CPM.2016.17,
  author =	{Carmel, Amir and Tsur, Dekel and Ziv-Ukelson, Michal},
  title =	{{On Almost Monge All Scores Matrices}},
  booktitle =	{27th Annual Symposium on Combinatorial Pattern Matching (CPM 2016)},
  pages =	{17:1--17:12},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-012-5},
  ISSN =	{1868-8969},
  year =	{2016},
  volume =	{54},
  editor =	{Grossi, Roberto and Lewenstein, Moshe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2016.17},
  URN =		{urn:nbn:de:0030-drops-60770},
  doi =		{10.4230/LIPIcs.CPM.2016.17},
  annote =	{Keywords: Sequence alignment, longest common subsequences, DIST matrices, Monge matrices, all path score computations.}
}
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