Frequent pattern mining with non-overlapping inversions

Da Jung Cho, Yo Sub Han, Hwee Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Frequent pattern mining is widely used in bioinformatics since frequent patterns in bio sequences often correspond to residues conserved during evolution. In bio sequence analysis, non-overlapping inversions are well-studied because of their practical properties for local sequence comparisons. We consider the problem of finding frequent patterns in a bio sequence with respect to non-overlapping inversions, and design efficient algorithms.

Original languageEnglish
Title of host publicationLanguage and Automata Theory and Applications - 9th International Conference, LATA 2015, Proceedings
EditorsAdrian-Horia Dediu, Carlos Martín-Vide, Enrico Formenti, Bianca Truthe
PublisherSpringer Verlag
Pages121-132
Number of pages12
ISBN (Electronic)9783319155784
DOIs
Publication statusPublished - 2015 Jan 1
Event9th International Conference on Language and Automata Theory and Applications, LATA 2015 - Nice, France
Duration: 2015 Mar 22015 Mar 6

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8977
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th International Conference on Language and Automata Theory and Applications, LATA 2015
CountryFrance
CityNice
Period15/3/215/3/6

Fingerprint

Frequent Pattern Mining
Frequent Pattern
Bioinformatics
Inversion
Sequence Comparison
Sequence Analysis
Efficient Algorithms
Design

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Cho, D. J., Han, Y. S., & Kim, H. (2015). Frequent pattern mining with non-overlapping inversions. In A-H. Dediu, C. Martín-Vide, E. Formenti, & B. Truthe (Eds.), Language and Automata Theory and Applications - 9th International Conference, LATA 2015, Proceedings (pp. 121-132). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8977). Springer Verlag. https://doi.org/10.1007/978-3-319-15579-1_9
Cho, Da Jung ; Han, Yo Sub ; Kim, Hwee. / Frequent pattern mining with non-overlapping inversions. Language and Automata Theory and Applications - 9th International Conference, LATA 2015, Proceedings. editor / Adrian-Horia Dediu ; Carlos Martín-Vide ; Enrico Formenti ; Bianca Truthe. Springer Verlag, 2015. pp. 121-132 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Cho, DJ, Han, YS & Kim, H 2015, Frequent pattern mining with non-overlapping inversions. in A-H Dediu, C Martín-Vide, E Formenti & B Truthe (eds), Language and Automata Theory and Applications - 9th International Conference, LATA 2015, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8977, Springer Verlag, pp. 121-132, 9th International Conference on Language and Automata Theory and Applications, LATA 2015, Nice, France, 15/3/2. https://doi.org/10.1007/978-3-319-15579-1_9

Frequent pattern mining with non-overlapping inversions. / Cho, Da Jung; Han, Yo Sub; Kim, Hwee.

Language and Automata Theory and Applications - 9th International Conference, LATA 2015, Proceedings. ed. / Adrian-Horia Dediu; Carlos Martín-Vide; Enrico Formenti; Bianca Truthe. Springer Verlag, 2015. p. 121-132 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8977).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Cho DJ, Han YS, Kim H. Frequent pattern mining with non-overlapping inversions. In Dediu A-H, Martín-Vide C, Formenti E, Truthe B, editors, Language and Automata Theory and Applications - 9th International Conference, LATA 2015, Proceedings. Springer Verlag. 2015. p. 121-132. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-15579-1_9