$$\textsc {McDag}$$ M C D A G : indexing maximal common subsequences for k strings
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...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-04-01
|
| Series: | Algorithms for Molecular Biology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13015-025-00271-z |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850146419627786240 |
|---|---|
| author | Giovanni Buzzega Alessio Conte Roberto Grossi Giulia Punzi |
| author_facet | Giovanni Buzzega Alessio Conte Roberto Grossi Giulia Punzi |
| author_sort | Giovanni Buzzega |
| collection | DOAJ |
| description | 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 $$\textsc {McDag}$$ M C D A G , 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. |
| format | Article |
| id | doaj-art-fbb0cec12c0a42f9a6e5ab9746b2a31c |
| institution | OA Journals |
| issn | 1748-7188 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | BMC |
| record_format | Article |
| series | Algorithms for Molecular Biology |
| spelling | doaj-art-fbb0cec12c0a42f9a6e5ab9746b2a31c2025-08-20T02:27:50ZengBMCAlgorithms for Molecular Biology1748-71882025-04-0120112110.1186/s13015-025-00271-z$$\textsc {McDag}$$ M C D A G : indexing maximal common subsequences for k stringsGiovanni Buzzega0Alessio Conte1Roberto Grossi2Giulia Punzi3Dipartimento di Informatica, Università di PisaDipartimento di Informatica, Università di PisaDipartimento di Informatica, Università di PisaDipartimento di Informatica, Università di PisaAbstract 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 $$\textsc {McDag}$$ M C D A G , 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.https://doi.org/10.1186/s13015-025-00271-zCommon subsequencesInclusion maximalityDirected acyclic graphIndex data structure |
| spellingShingle | Giovanni Buzzega Alessio Conte Roberto Grossi Giulia Punzi $$\textsc {McDag}$$ M C D A G : indexing maximal common subsequences for k strings Algorithms for Molecular Biology Common subsequences Inclusion maximality Directed acyclic graph Index data structure |
| title | $$\textsc {McDag}$$ M C D A G : indexing maximal common subsequences for k strings |
| title_full | $$\textsc {McDag}$$ M C D A G : indexing maximal common subsequences for k strings |
| title_fullStr | $$\textsc {McDag}$$ M C D A G : indexing maximal common subsequences for k strings |
| title_full_unstemmed | $$\textsc {McDag}$$ M C D A G : indexing maximal common subsequences for k strings |
| title_short | $$\textsc {McDag}$$ M C D A G : indexing maximal common subsequences for k strings |
| title_sort | textsc mcdag m c d a g indexing maximal common subsequences for k strings |
| topic | Common subsequences Inclusion maximality Directed acyclic graph Index data structure |
| url | https://doi.org/10.1186/s13015-025-00271-z |
| work_keys_str_mv | AT giovannibuzzega textscmcdagmcdagindexingmaximalcommonsubsequencesforkstrings AT alessioconte textscmcdagmcdagindexingmaximalcommonsubsequencesforkstrings AT robertogrossi textscmcdagmcdagindexingmaximalcommonsubsequencesforkstrings AT giuliapunzi textscmcdagmcdagindexingmaximalcommonsubsequencesforkstrings |