8 Search Results for "Rosone, Giovanna"

Document
DOI: 10.4230/LIPIcs.WABI.2022.23
phyBWT: Alignment-Free Phylogeny via eBWT Positional Clustering

Authors: Veronica Guerrini, Alessio Conte, Roberto Grossi, Gianni Liti, Giovanna Rosone, and Lorenzo Tattini

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

Abstract
Molecular phylogenetics is a fundamental branch of biology. It studies the evolutionary relationships among the individuals of a population through their biological sequences, and may provide insights about the origin and the evolution of viral diseases, or highlight complex evolutionary trajectories. In this paper we develop a method called phyBWT, describing how to use the extended Burrows-Wheeler Transform (eBWT) for a collection of DNA sequences to directly reconstruct phylogeny, bypassing the alignment against a reference genome or de novo assembly. Our phyBWT hinges on the combinatorial properties of the eBWT positional clustering framework. We employ eBWT to detect relevant blocks of the longest shared substrings of varying length (unlike the k-mer-based approaches that need to fix the length k a priori), and build a suitable decomposition leading to a phylogenetic tree, step by step. As a result, phyBWT is a new alignment-, assembly-, and reference-free method that builds a partition tree without relying on the pairwise comparison of sequences, thus avoiding to use a distance matrix to infer phylogeny. The preliminary experimental results on sequencing data show that our method can handle datasets of different types (short reads, contigs, or entire genomes), producing trees of quality comparable to that found in the benchmark phylogeny.
Cite as

Veronica Guerrini, Alessio Conte, Roberto Grossi, Gianni Liti, Giovanna Rosone, and Lorenzo Tattini. phyBWT: Alignment-Free Phylogeny via eBWT Positional Clustering. In 22nd International Workshop on Algorithms in Bioinformatics (WABI 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 242, pp. 23:1-23:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{guerrini_et_al:LIPIcs.WABI.2022.23,
  author =	{Guerrini, Veronica and Conte, Alessio and Grossi, Roberto and Liti, Gianni and Rosone, Giovanna and Tattini, Lorenzo},
  title =	{{phyBWT: Alignment-Free Phylogeny via eBWT Positional Clustering}},
  booktitle =	{22nd International Workshop on Algorithms in Bioinformatics (WABI 2022)},
  pages =	{23:1--23:19},
  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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2022.23},
  URN =		{urn:nbn:de:0030-drops-170577},
  doi =		{10.4230/LIPIcs.WABI.2022.23},
  annote =	{Keywords: Phylogeny, partition tree, BWT, positional cluster, alignment-free, reference-free, assembly-free}
}
Document
DOI: 10.4230/LIPIcs.WABI.2021.13
Compressing and Indexing Aligned Readsets

Authors: Travis Gagie, Garance Gourdel, and Giovanni Manzini

Published in: LIPIcs, Volume 201, 21st International Workshop on Algorithms in Bioinformatics (WABI 2021)

Abstract
Compressed full-text indexes are one of the main success stories of bioinformatics data structures but even they struggle to handle some DNA readsets. This may seem surprising since, at least when dealing with short reads from the same individual, the readset will be highly repetitive and, thus, highly compressible. If we are not careful, however, this advantage can be more than offset by two disadvantages: first, since most base pairs are included in at least tens reads each, the uncompressed readset is likely to be at least an order of magnitude larger than the individual’s uncompressed genome; second, these indexes usually pay some space overhead for each string they store, and the total overhead can be substantial when dealing with millions of reads. The most successful compressed full-text indexes for readsets so far are based on the Extended Burrows-Wheeler Transform (EBWT) and use a sorting heuristic to try to reduce the space overhead per read, but they still treat the reads as separate strings and thus may not take full advantage of the readset’s structure. For example, if we have already assembled an individual’s genome from the readset, then we can usually use it to compress the readset well: e.g., we store the gap-coded list of reads' starting positions; we store the list of their lengths, which is often highly compressible; and we store information about the sequencing errors, which are rare with short reads. There is nowhere, however, where we can plug an assembled genome into the EBWT. In this paper we show how to use one or more assembled or partially assembled genome as the basis for a compressed full-text index of its readset. Specifically, we build a labelled tree by taking the assembled genome as a trunk and grafting onto it the reads that align to it, at the starting positions of their alignments. Next, we compute the eXtended Burrows-Wheeler Transform (XBWT) of the resulting labelled tree and build a compressed full-text index on that. Although this index can occasionally return false positives, it is usually much more compact than the alternatives. Following the established practice for datasets with many repetitions, we compare different full-text indices by looking at the number of runs in the transformed strings. For a human Chr19 readset our preliminary experiments show that eliminating separators characters from the EBWT reduces the number of runs by 19%, from 220 million to 178 million, and using the XBWT reduces it by a further 15%, to 150 million.
Cite as

Travis Gagie, Garance Gourdel, and Giovanni Manzini. Compressing and Indexing Aligned Readsets. In 21st International Workshop on Algorithms in Bioinformatics (WABI 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 201, pp. 13:1-13:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{gagie_et_al:LIPIcs.WABI.2021.13,
  author =	{Gagie, Travis and Gourdel, Garance and Manzini, Giovanni},
  title =	{{Compressing and Indexing Aligned Readsets}},
  booktitle =	{21st International Workshop on Algorithms in Bioinformatics (WABI 2021)},
  pages =	{13:1--13:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-200-6},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{201},
  editor =	{Carbone, Alessandra and El-Kebir, Mohammed},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2021.13},
  URN =		{urn:nbn:de:0030-drops-143660},
  doi =		{10.4230/LIPIcs.WABI.2021.13},
  annote =	{Keywords: data compression, compact data structures, FM-index, Burrows-Wheeler Transform, EBWT, XBWT, DNA reads}
}
Document
Track A: Algorithms, Complexity and Games
DOI: 10.4230/LIPIcs.ICALP.2019.21
Even Faster Elastic-Degenerate String Matching via Fast Matrix Multiplication

Authors: Giulia Bernardini, Paweł Gawrychowski, Nadia Pisanti, Solon P. Pissis, and Giovanna Rosone

Published in: LIPIcs, Volume 132, 46th International Colloquium on Automata, Languages, and Programming (ICALP 2019)

Abstract
An elastic-degenerate (ED) string is a sequence of n sets of strings of total length N, which was recently proposed to model a set of similar sequences. The ED string matching (EDSM) problem is to find all occurrences of a pattern of length m in an ED text. The EDSM problem has recently received some attention in the combinatorial pattern matching community, and an O(nm^{1.5}sqrt{log m} + N)-time algorithm is known [Aoyama et al., CPM 2018]. The standard assumption in the prior work on this question is that N is substantially larger than both n and m, and thus we would like to have a linear dependency on the former. Under this assumption, the natural open problem is whether we can decrease the 1.5 exponent in the time complexity, similarly as in the related (but, to the best of our knowledge, not equivalent) word break problem [Backurs and Indyk, FOCS 2016]. Our starting point is a conditional lower bound for the EDSM problem. We use the popular combinatorial Boolean matrix multiplication (BMM) conjecture stating that there is no truly subcubic combinatorial algorithm for BMM [Abboud and Williams, FOCS 2014]. By designing an appropriate reduction we show that a combinatorial algorithm solving the EDSM problem in O(nm^{1.5-epsilon} + N) time, for any epsilon>0, refutes this conjecture. Of course, the notion of combinatorial algorithms is not clearly defined, so our reduction should be understood as an indication that decreasing the exponent requires fast matrix multiplication. Two standard tools used in algorithms on strings are string periodicity and fast Fourier transform. Our main technical contribution is that we successfully combine these tools with fast matrix multiplication to design a non-combinatorial O(nm^{1.381} + N)-time algorithm for EDSM. To the best of our knowledge, we are the first to do so.
Cite as

Giulia Bernardini, Paweł Gawrychowski, Nadia Pisanti, Solon P. Pissis, and Giovanna Rosone. Even Faster Elastic-Degenerate String Matching via Fast Matrix Multiplication. In 46th International Colloquium on Automata, Languages, and Programming (ICALP 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 132, pp. 21:1-21:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{bernardini_et_al:LIPIcs.ICALP.2019.21,
  author =	{Bernardini, Giulia and Gawrychowski, Pawe{\l} and Pisanti, Nadia and Pissis, Solon P. and Rosone, Giovanna},
  title =	{{Even Faster Elastic-Degenerate String Matching via Fast Matrix Multiplication}},
  booktitle =	{46th International Colloquium on Automata, Languages, and Programming (ICALP 2019)},
  pages =	{21:1--21:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-109-2},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{132},
  editor =	{Baier, Christel and Chatzigiannakis, Ioannis and Flocchini, Paola and Leonardi, Stefano},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2019.21},
  URN =		{urn:nbn:de:0030-drops-105973},
  doi =		{10.4230/LIPIcs.ICALP.2019.21},
  annote =	{Keywords: string algorithms, pattern matching, elastic-degenerate string, matrix multiplication, fast Fourier transform}
}
Document
DOI: 10.4230/LIPIcs.CPM.2019.7
Space-Efficient Computation of the LCP Array from the Burrows-Wheeler Transform

Authors: Nicola Prezza and Giovanna Rosone

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

Abstract
We show that the Longest Common Prefix Array of a text collection of total size n on alphabet [1,sigma] can be computed from the Burrows-Wheeler transformed collection in O(n log sigma) time using o(n log sigma) bits of working space on top of the input and output. Our result improves (on small alphabets) and generalizes (to string collections) the previous solution from Beller et al., which required O(n) bits of extra working space. We also show how to merge the BWTs of two collections of total size n within the same time and space bounds. The procedure at the core of our algorithms can be used to enumerate suffix tree intervals in succinct space from the BWT, which is of independent interest. An engineered implementation of our first algorithm on DNA alphabet induces the LCP of a large (16 GiB) collection of short (100 bases) reads at a rate of 2.92 megabases per second using in total 1.5 Bytes per base in RAM. Our second algorithm merges the BWTs of two short-reads collections of 8 GiB each at a rate of 1.7 megabases per second and uses 0.625 Bytes per base in RAM. An extension of this algorithm that computes also the LCP array of the merged collection processes the data at a rate of 1.48 megabases per second and uses 1.625 Bytes per base in RAM.
Cite as

Nicola Prezza and Giovanna Rosone. Space-Efficient Computation of the LCP Array from the Burrows-Wheeler Transform. In 30th Annual Symposium on Combinatorial Pattern Matching (CPM 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 128, pp. 7:1-7:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{prezza_et_al:LIPIcs.CPM.2019.7,
  author =	{Prezza, Nicola and Rosone, Giovanna},
  title =	{{Space-Efficient Computation of the LCP Array from the Burrows-Wheeler Transform}},
  booktitle =	{30th Annual Symposium on Combinatorial Pattern Matching (CPM 2019)},
  pages =	{7:1--7:18},
  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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2019.7},
  URN =		{urn:nbn:de:0030-drops-104782},
  doi =		{10.4230/LIPIcs.CPM.2019.7},
  annote =	{Keywords: Burrows-Wheeler Transform, LCP array, DNA reads}
}
Document
DOI: 10.4230/LIPIcs.CPM.2019.12
A New Class of Searchable and Provably Highly Compressible String Transformations

Authors: Raffaele Giancarlo, Giovanni Manzini, Giovanna Rosone, and Marinella Sciortino

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

Abstract
The Burrows-Wheeler Transform is a string transformation that plays a fundamental role for the design of self-indexing compressed data structures. Over the years, researchers have successfully extended this transformation outside the domains of strings. However, efforts to find non-trivial alternatives of the original, now 25 years old, Burrows-Wheeler string transformation have met limited success. In this paper we bring new lymph to this area by introducing a whole new family of transformations that have all the "myriad virtues" of the BWT: they can be computed and inverted in linear time, they produce provably highly compressible strings, and they support linear time pattern search directly on the transformed string. This new family is a special case of a more general class of transformations based on context adaptive alphabet orderings, a concept introduced here. This more general class includes also the Alternating BWT, another invertible string transforms recently introduced in connection with a generalization of Lyndon words.
Cite as

Raffaele Giancarlo, Giovanni Manzini, Giovanna Rosone, and Marinella Sciortino. A New Class of Searchable and Provably Highly Compressible String Transformations. In 30th Annual Symposium on Combinatorial Pattern Matching (CPM 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 128, pp. 12:1-12:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{giancarlo_et_al:LIPIcs.CPM.2019.12,
  author =	{Giancarlo, Raffaele and Manzini, Giovanni and Rosone, Giovanna and Sciortino, Marinella},
  title =	{{A New Class of Searchable and Provably Highly Compressible String Transformations}},
  booktitle =	{30th Annual Symposium on Combinatorial Pattern Matching (CPM 2019)},
  pages =	{12:1--12:12},
  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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2019.12},
  URN =		{urn:nbn:de:0030-drops-104833},
  doi =		{10.4230/LIPIcs.CPM.2019.12},
  annote =	{Keywords: Data Indexing and Compression, Burrows-Wheeler Transformation, Combinatorics on Words}
}
Document
DOI: 10.4230/LIPIcs.WABI.2018.3
Detecting Mutations by eBWT

Authors: Nicola Prezza, Nadia Pisanti, Marinella Sciortino, and Giovanna Rosone

Published in: LIPIcs, Volume 113, 18th International Workshop on Algorithms in Bioinformatics (WABI 2018)

Abstract
In this paper we develop a theory describing how the extended Burrows-Wheeler Transform (eBWT) of a collection of DNA fragments tends to cluster together the copies of nucleotides sequenced from a genome G. Our theory accurately predicts how many copies of any nucleotide are expected inside each such cluster, and how an elegant and precise LCP array based procedure can locate these clusters in the eBWT. Our findings are very general and can be applied to a wide range of different problems. In this paper, we consider the case of alignment-free and reference-free SNPs discovery in multiple collections of reads. We note that, in accordance with our theoretical results, SNPs are clustered in the eBWT of the reads collection, and we develop a tool finding SNPs with a simple scan of the eBWT and LCP arrays. Preliminary results show that our method requires much less coverage than state-of-the-art tools while drastically improving precision and sensitivity.
Cite as

Nicola Prezza, Nadia Pisanti, Marinella Sciortino, and Giovanna Rosone. Detecting Mutations by eBWT. In 18th International Workshop on Algorithms in Bioinformatics (WABI 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 113, pp. 3:1-3:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{prezza_et_al:LIPIcs.WABI.2018.3,
  author =	{Prezza, Nicola and Pisanti, Nadia and Sciortino, Marinella and Rosone, Giovanna},
  title =	{{Detecting Mutations by eBWT}},
  booktitle =	{18th International Workshop on Algorithms in Bioinformatics (WABI 2018)},
  pages =	{3:1--3:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-082-8},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{113},
  editor =	{Parida, Laxmi and Ukkonen, Esko},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2018.3},
  URN =		{urn:nbn:de:0030-drops-93051},
  doi =		{10.4230/LIPIcs.WABI.2018.3},
  annote =	{Keywords: BWT, LCP Array, SNPs, Reference-free, Assembly-free}
}
Document
DOI: 10.4230/LIPIcs.WABI.2018.21
Degenerate String Comparison and Applications

Authors: Mai Alzamel, Lorraine A. K. Ayad, Giulia Bernardini, Roberto Grossi, Costas S. Iliopoulos, Nadia Pisanti, Solon P. Pissis, and Giovanna Rosone

Published in: LIPIcs, Volume 113, 18th International Workshop on Algorithms in Bioinformatics (WABI 2018)

Abstract
A generalised degenerate string (GD string) S^ is a sequence of n sets of strings of total size N, where the ith set contains strings of the same length k_i but this length can vary between different sets. We denote the sum of these lengths k_0, k_1,...,k_{n-1} by W. This type of uncertain sequence can represent, for example, a gapless multiple sequence alignment of width W in a compact form. Our first result in this paper is an O(N+M)-time algorithm for deciding whether the intersection of two GD strings of total sizes N and M, respectively, over an integer alphabet, is non-empty. This result is based on a combinatorial result of independent interest: although the intersection of two GD strings can be exponential in the total size of the two strings, it can be represented in only linear space. A similar result can be obtained by employing an automata-based approach but its cost is alphabet-dependent. We then apply our string comparison algorithm to compute palindromes in GD strings. We present an O(min{W,n^2}N)-time algorithm for computing all palindromes in S^. Furthermore, we show a similar conditional lower bound for computing maximal palindromes in S^. Finally, proof-of-concept experimental results are presented using real protein datasets.
Cite as

Mai Alzamel, Lorraine A. K. Ayad, Giulia Bernardini, Roberto Grossi, Costas S. Iliopoulos, Nadia Pisanti, Solon P. Pissis, and Giovanna Rosone. Degenerate String Comparison and Applications. In 18th International Workshop on Algorithms in Bioinformatics (WABI 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 113, pp. 21:1-21:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{alzamel_et_al:LIPIcs.WABI.2018.21,
  author =	{Alzamel, Mai and Ayad, Lorraine A. K. and Bernardini, Giulia and Grossi, Roberto and Iliopoulos, Costas S. and Pisanti, Nadia and Pissis, Solon P. and Rosone, Giovanna},
  title =	{{Degenerate String Comparison and Applications}},
  booktitle =	{18th International Workshop on Algorithms in Bioinformatics (WABI 2018)},
  pages =	{21:1--21:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-082-8},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{113},
  editor =	{Parida, Laxmi and Ukkonen, Esko},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2018.21},
  URN =		{urn:nbn:de:0030-drops-93236},
  doi =		{10.4230/LIPIcs.WABI.2018.21},
  annote =	{Keywords: degenerate strings, generalised degenerate strings, elastic-degenerate strings, string comparison, palindromes}
}
Document
DOI: 10.4230/LIPIcs.CPM.2017.9
On-Line Pattern Matching on Similar Texts

Authors: Roberto Grossi, Costas S. Iliopoulos, Chang Liu, Nadia Pisanti, Solon P. Pissis, Ahmad Retha, Giovanna Rosone, Fatima Vayani, and Luca Versari

Published in: LIPIcs, Volume 78, 28th Annual Symposium on Combinatorial Pattern Matching (CPM 2017)

Abstract
Pattern matching on a set of similar texts has received much attention, especially recently, mainly due to its application in cataloguing human genetic variation. In particular, many different algorithms have been proposed for the off-line version of this problem; that is, constructing a compressed index for a set of similar texts in order to answer pattern matching queries efficiently. However, the on-line, more fundamental, version of this problem is a rather undeveloped topic. Solutions to the on-line version can be beneficial for a number of reasons; for instance, efficient on-line solutions can be used in combination with partial indexes as practical trade-offs. We make here an attempt to close this gap via proposing two efficient algorithms for this problem. Notably, one of the algorithms requires time linear in the size of the texts' representation, for short patterns. Furthermore, experimental results confirm our theoretical findings in practical terms.
Cite as

Roberto Grossi, Costas S. Iliopoulos, Chang Liu, Nadia Pisanti, Solon P. Pissis, Ahmad Retha, Giovanna Rosone, Fatima Vayani, and Luca Versari. On-Line Pattern Matching on Similar Texts. In 28th Annual Symposium on Combinatorial Pattern Matching (CPM 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 78, pp. 9:1-9:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{grossi_et_al:LIPIcs.CPM.2017.9,
  author =	{Grossi, Roberto and Iliopoulos, Costas S. and Liu, Chang and Pisanti, Nadia and Pissis, Solon P. and Retha, Ahmad and Rosone, Giovanna and Vayani, Fatima and Versari, Luca},
  title =	{{On-Line Pattern Matching on Similar Texts}},
  booktitle =	{28th Annual Symposium on Combinatorial Pattern Matching (CPM 2017)},
  pages =	{9:1--9:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-039-2},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{78},
  editor =	{K\"{a}rkk\"{a}inen, Juha and Radoszewski, Jakub and Rytter, Wojciech},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2017.9},
  URN =		{urn:nbn:de:0030-drops-73379},
  doi =		{10.4230/LIPIcs.CPM.2017.9},
  annote =	{Keywords: string algorithms, pattern matching, degenerate strings, elastic-degenerate strings, on-line algorithms}
}
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