A non-deterministic grammar inference algorithm applied to the cleavage site prediction problem in bioinformatics

Gloria Inés Alvarez; Jorge Hernán Victoria; Enrique Bravo; Pedro García

doi:10.1007/978-3-642-15488-1_23

A non-deterministic grammar inference algorithm applied to the cleavage site prediction problem in bioinformatics

Gloria Inés Alvarez, Jorge Hernán Victoria, Enrique Bravo, Pedro García

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

We report results on applying the OIL (Order Independent Language) grammar inference algorithm to predict cleavage sites in polyproteins from translation of Potivirus genome. This non-deterministic algorithm is used to generate a group of models which vote to predict the occurrence of the pattern. We built nine models, one for each cleavage site in this kind of virus genome and report sensibility, specificity, accuracy for each model. Our results show that this technique is useful to predict cleavage sites in the given task with accuracy rates higher than 95%.

Original language	English
Title of host publication	Grammatical Inference
Subtitle of host publication	Theoretical Results and Applications - 10th International Colloquium, ICGI 2010, Proceedings
Pages	267-270
Number of pages	4
DOIs	https://doi.org/10.1007/978-3-642-15488-1_23
State	Published - 2010
Event	10th International Colloquium on Grammatical Inference, ICGI 2010 - Valencia, Spain Duration: 13 Sep 2010 → 16 Sep 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6339 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	10th International Colloquium on Grammatical Inference, ICGI 2010
Country/Territory	Spain
City	Valencia
Period	13/09/10 → 16/09/10

Access to Document

10.1007/978-3-642-15488-1_23

Cite this

Alvarez, G. I., Victoria, J. H., Bravo, E., & García, P. (2010). A non-deterministic grammar inference algorithm applied to the cleavage site prediction problem in bioinformatics. In Grammatical Inference: Theoretical Results and Applications - 10th International Colloquium, ICGI 2010, Proceedings (pp. 267-270). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6339 LNAI). https://doi.org/10.1007/978-3-642-15488-1_23

Alvarez, Gloria Inés ; Victoria, Jorge Hernán ; Bravo, Enrique et al. / A non-deterministic grammar inference algorithm applied to the cleavage site prediction problem in bioinformatics. Grammatical Inference: Theoretical Results and Applications - 10th International Colloquium, ICGI 2010, Proceedings. 2010. pp. 267-270 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{489a3f0da6714fa1bebab082d9b3f911,

title = "A non-deterministic grammar inference algorithm applied to the cleavage site prediction problem in bioinformatics",

abstract = "We report results on applying the OIL (Order Independent Language) grammar inference algorithm to predict cleavage sites in polyproteins from translation of Potivirus genome. This non-deterministic algorithm is used to generate a group of models which vote to predict the occurrence of the pattern. We built nine models, one for each cleavage site in this kind of virus genome and report sensibility, specificity, accuracy for each model. Our results show that this technique is useful to predict cleavage sites in the given task with accuracy rates higher than 95%.",

author = "Alvarez, {Gloria In{\'e}s} and Victoria, {Jorge Hern{\'a}n} and Enrique Bravo and Pedro Garc{\'i}a",

note = "Funding Information: This work was partially supported by the Spanish Ministry of Education and Science TIN2007-60769.; 10th International Colloquium on Grammatical Inference, ICGI 2010 ; Conference date: 13-09-2010 Through 16-09-2010",

year = "2010",

doi = "10.1007/978-3-642-15488-1_23",

language = "English",

isbn = "3642154875",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "267--270",

booktitle = "Grammatical Inference",

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Alvarez, GI, Victoria, JH, Bravo, E & García, P 2010, A non-deterministic grammar inference algorithm applied to the cleavage site prediction problem in bioinformatics. in Grammatical Inference: Theoretical Results and Applications - 10th International Colloquium, ICGI 2010, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6339 LNAI, pp. 267-270, 10th International Colloquium on Grammatical Inference, ICGI 2010, Valencia, Spain, 13/09/10. https://doi.org/10.1007/978-3-642-15488-1_23

A non-deterministic grammar inference algorithm applied to the cleavage site prediction problem in bioinformatics. / Alvarez, Gloria Inés; Victoria, Jorge Hernán; Bravo, Enrique et al.
Grammatical Inference: Theoretical Results and Applications - 10th International Colloquium, ICGI 2010, Proceedings. 2010. p. 267-270 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6339 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A non-deterministic grammar inference algorithm applied to the cleavage site prediction problem in bioinformatics

AU - Alvarez, Gloria Inés

AU - Victoria, Jorge Hernán

AU - Bravo, Enrique

AU - García, Pedro

N1 - Funding Information: This work was partially supported by the Spanish Ministry of Education and Science TIN2007-60769.

PY - 2010

Y1 - 2010

N2 - We report results on applying the OIL (Order Independent Language) grammar inference algorithm to predict cleavage sites in polyproteins from translation of Potivirus genome. This non-deterministic algorithm is used to generate a group of models which vote to predict the occurrence of the pattern. We built nine models, one for each cleavage site in this kind of virus genome and report sensibility, specificity, accuracy for each model. Our results show that this technique is useful to predict cleavage sites in the given task with accuracy rates higher than 95%.

AB - We report results on applying the OIL (Order Independent Language) grammar inference algorithm to predict cleavage sites in polyproteins from translation of Potivirus genome. This non-deterministic algorithm is used to generate a group of models which vote to predict the occurrence of the pattern. We built nine models, one for each cleavage site in this kind of virus genome and report sensibility, specificity, accuracy for each model. Our results show that this technique is useful to predict cleavage sites in the given task with accuracy rates higher than 95%.

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U2 - 10.1007/978-3-642-15488-1_23

DO - 10.1007/978-3-642-15488-1_23

M3 - Conference contribution

AN - SCOPUS:78149245591

SN - 3642154875

SN - 9783642154874

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 267

EP - 270

BT - Grammatical Inference

T2 - 10th International Colloquium on Grammatical Inference, ICGI 2010

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Alvarez GI, Victoria JH, Bravo E, García P. A non-deterministic grammar inference algorithm applied to the cleavage site prediction problem in bioinformatics. In Grammatical Inference: Theoretical Results and Applications - 10th International Colloquium, ICGI 2010, Proceedings. 2010. p. 267-270. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-15488-1_23

A non-deterministic grammar inference algorithm applied to the cleavage site prediction problem in bioinformatics

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