The Burrows–Wheeler similarity distribution between biological sequences based on Burrows–Wheeler transform

Yang, Lianping; Zhang, Xiangde; Wang, Tianming

doi:10.1016/j.jtbi.2009.10.033

Cited by 25 publications

(14 citation statements)

References 57 publications

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“…If one sequence which is given the information contained in the other sequence is significantly compressible, the two sequences are considered to be close. There are also some important methods which are based on compression algorithm but do not actually apply the compression, such as Lemple-Ziv complexity and Burrows-Wheeler transform (Otu and Sayood, 2003;Mantaci et al, 2007Mantaci et al, , 2008Yang et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

New method for comparing DNA primary sequences based on a discrimination measure

Feng

Park

et al. 2010

Journal of Theoretical Biology

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We introduce a new approach to compare DNA primary sequences. The core of our method is a new measure of pairwise distances among sequences. Using the primitive discrimination substrings of sequence S and Q, a discrimination measure DM(S, Q) is defined for the similarity analysis of them. The proposed method does not require multiple alignments and is fully automatic. To illustrate its utility, we construct phylogenetic trees on two independent data sets. The results indicate that the method is efficient and powerful.

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Section: Introductionmentioning

confidence: 99%

New method for comparing DNA primary sequences based on a discrimination measure

Feng

Park

et al. 2010

Journal of Theoretical Biology

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“…Such capabilities of the BW T have originated the field of Compressed Full-text Self-indices [29,38]. The remarkable properties of the BW T have aroused great interest both from the theoretical and applicative points of view [30,31,35,48,27,7,26,44,17,40].…”

Section: Introductionmentioning

confidence: 99%

The Alternating BWT: An algorithmic perspective

Giancarlo

Manzini

Restivo

et al. 2020

Theoretical Computer Science

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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, with important applications in several area in science and engineering. The Alternating Burrows-Wheeler Transform (ABWT) is another transformation recently introduced in [Gessel et al. 2012] and studied in the field of Combinatorics on Words. It is analogous to the BWT, except that it uses an alternating lexicographical order instead of the usual one. Building on results in [Giancarlo et al. 2018], where we have shown that BWT and ABWT are part of a larger class of reversible transformations, here we provide a combinatorial and algorithmic study of the novel transform ABWT. We establish a deep analogy between BWT and ABWT by proving they are the only ones in the above mentioned class to be rank-invertible, a novel notion guaranteeing efficient invertibility. In addition, we show that the backward-search procedure can be efficiently generalized to the ABWT; this result implies that also the ABWT can be used as a basis for efficient compressed full text indices. Finally, we prove that the ABWT can be efficiently computed by using a combination of the Difference Cover suffix sorting algorithm [Kärkkäinen et al., 2006] with a linear time algorithm for finding the minimal cyclic rotation of a word with respect to the alternating lexicographical order.

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“…A class of similarity measures was defined by Mantaci et al [17] over an extension of the Burrows-Wheeler transform for string collections, called eBWT [16]. Later, Yang et al [34,35] recrafted the method by Mantaci et al and introduced the Burrows-Wheeler similarity distribution (BWSD) of two strings S 1 and S 2 based on the BWT of their concatenation. The authors evaluated similarity measures based on the expectation and Shannon entropy of the BWSD to efficiently construct phylogenetic trees for DNA and protein sequences, thus contributing to an alternative to alignment-based similarity measure among biological sequences.…”

Section: Introductionmentioning

confidence: 99%

“…In this article we present two new algorithms to compute the Burrows-Wheeler similarity distribution and we show how to efficiently compute BWSDbased distances among all pairs of strings in a collection. Our algorithms compute the BWT for the concatenation of all strings only once, instead of the pairwise construction of BWTs proposed by Yang [34,35], and use compressed data structures that allow reductions of the running time while still keeping a small memory usage, as shown by a set of experiments with real and artificial datasets. We also present both space-efficient alternatives and parallel versions of our algorithms, that achieved good time/space trade-off and speedup factors in our experiments, thus enabling the evaluation of the measure at larger scales.…”

Section: Introductionmentioning

confidence: 99%

Algorithms to compute the Burrows-Wheeler Similarity Distribution

Louza

Telles

Gog

et al. 2019

Theoretical Computer Science

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The Burrows-Wheeler transform (BWT) is a well studied text transformation widely used in data compression and text indexing. The BWT of two strings can also provide similarity measures between them, based on the observation that the more their symbols are intermixed in the transformation, the more the strings are similar. In this article we present two new algorithms to compute similarity measures based on the BWT for string collections. In particular, we present practical and theoretical improvements to the computation of the Burrows-Wheeler similarity distribution for all pairs of strings in a collection. Our algorithms take advantage of the BWT computed for the concatenation of all strings, and use compressed data structures that allow reducing the running time with a small memory footprint, as shown by a set of experiments with real and artificial datasets.

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The Burrows–Wheeler similarity distribution between biological sequences based on Burrows–Wheeler transform

Cited by 25 publications

References 57 publications

New method for comparing DNA primary sequences based on a discrimination measure

New method for comparing DNA primary sequences based on a discrimination measure

The Alternating BWT: An algorithmic perspective

Algorithms to compute the Burrows-Wheeler Similarity Distribution

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