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20122025
most citedLarge-scale compression of genomic sequence databases with the Burrows-Wheeler transform

145 citations · 240 across the 14 of their papers we have counts for

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Showing 2019Show all

7 papers · 1 filter

cs.DS2019

Space-Efficient Construction of Compressed Suffix Trees

Nicola Prezza, Giovanna Rosone

We show how to build several data structures of central importance to string processing, taking as input the Burrows-Wheeler transform (BWT) and using small extra working space. Le…

cs.DS2019★ 4 cited

String Attractors and Combinatorics on Words

Sabrina Mantaci, Antonio Restivo, Giuseppe Romana +2

The notion of \emph{string attractor} has recently been introduced in [Prezza, 2017] and studied in [Kempa and Prezza, 2018] to provide a unifying framework for known dictionary-ba…

cs.DS2019

The Alternating BWT: an algorithmic perspective

Raffaele Giancarlo, Giovanni Manzini, Antonio Restivo +2

The Burrows-Wheeler Transform (BWT) is a word transformation introduced in 1994 for Data Compression. It has become a fundamental tool for designing self-indexing data structures,…

cs.DS2019

Combinatorial Algorithms for String Sanitization

Giulia Bernardini, Huiping Chen, Alessio Conte +6

String data are often disseminated to support applications such as location-based service provision or DNA sequence analysis. This dissemination, however, may expose sensitive patt…

cs.DS2019

Elastic-Degenerate String Matching via Fast Matrix Multiplication

Giulia Bernardini, Paweł Gawrychowski, Nadia Pisanti +2

An elastic-degenerate (ED) string is a sequence of sets of strings of total length , which was recently proposed to model a set of similar sequences. The ED string matching…

cs.DS2019★ 3 cited

A New Class of Searchable and Provably Highly Compressible String Transformations

Raffaele Giancarlo, Giovanni Manzini, Giovanna Rosone +1

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…