$$\textsc {McDag}$$: indexing maximal common subsequences for k strings

Analyzing and comparing sequences of symbols is among the most fundamental problems in computer science, possibly even more so in bioinformatics. Maximal Common Subsequences (MCSs), i.e., inclusion-maximal sequences of non-contiguous symbols common to two or more strings, have only recently received attention in this area, despite being a basic notion and a natural generalization of more common tools like Longest Common Substrings/Subsequences. In this paper we simplify and engineer recent advancements in MCSs into a practical tool called <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>M</mml:mi> <mml:mstyle><mml:mi>C</mml:mi> <mml:mi>D</mml:mi> <mml:mi>A</mml:mi> <mml:mi>G</mml:mi></mml:mstyle> </mml:mrow> </mml:math> , the first publicly available tool that can index MCSs of real genomic data, and show that its definition can be generalized to multiple strings. We demonstrate that our tool can index pairs of sequences exceeding 10,000 base pairs within minutes, utilizing only 4-7% more than the minimum required nodes. For three or more sequences, we observe experimentally that the minimum index may exhibit a significant increase in the number of nodes.

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Publication Details

Journal
Algorithms for Molecular Biology
Published
2025-04-19
DOI
https://doi.org/10.1186/s13015-025-00271-z
Primary Topic
Algorithms and Data Compression
Type
article
Field-Weighted Citation Impact
0.00

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article

$$\textsc {McDag}$$: indexing maximal common subsequences for k strings

Roberto Grossi, Giovanni Buzzega, Alessio Conte, Giulia Punzi
Algorithms for Molecular Biology
Algorithms and Data Compression
article

$$\textsc {McDag}$$: indexing maximal common subsequences for k strings

Roberto Grossi, Giovanni Buzzega, Alessio Conte, Giulia Punzi
article en

Abstract

Analyzing and comparing sequences of symbols is among the most fundamental problems in computer science, possibly even more so in bioinformatics. Maximal Common Subsequences (MCSs), i.e., inclusion-maximal sequences of non-contiguous symbols common to two or more strings, have only recently received attention in this area, despite being a basic notion and a natural generalization of more common tools like Longest Common Substrings/Subsequences. In this paper we simplify and engineer recent advancements in MCSs into a practical tool called <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>M</mml:mi> <mml:mstyle><mml:mi>C</mml:mi> <mml:mi>D</mml:mi> <mml:mi>A</mml:mi> <mml:mi>G</mml:mi></mml:mstyle> </mml:mrow> </mml:math> , the first publicly available tool that can index MCSs of real genomic data, and show that its definition can be generalized to multiple strings. We demonstrate that our tool can index pairs of sequences exceeding 10,000 base pairs within minutes, utilizing only 4-7% more than the minimum required nodes. For three or more sequences, we observe experimentally that the minimum index may exhibit a significant increase in the number of nodes.

Algorithms for Molecular BiologyVol. 20(1)
University of Pisa (IT)
European Commission, Ministero dell’Istruzione, dell’Università e della Ricerca, Horizon 2020
Quality Education
Openalex Percentile: Top 96%
Algorithms and Data Compression
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$\textsc {McDag}$: indexing maximal common subsequences for k strings — Roberto Grossi, Giovanni Buzzega, et al. · Algorithms for Molecular Biology (2025) | TGRS Research Map | TGRS