An evolving automaton for RNA secondary structure prediction

Carlos A.M. Del Carpio; Mohamed Ismael; Eichiro Ichiishi; Michihisa Koyama; Momoji Kubo; Akira Miyamoto

doi:10.1109/ijcnn.2006.247018

An evolving automaton for RNA secondary structure prediction

Carlos A.M. Del Carpio, Mohamed Ismael, Eichiro Ichiishi, Michihisa Koyama, Momoji Kubo, Akira Miyamoto

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

Abstract

Conventional methods for RNA 2D structure prediction search for minimal free energy structures. RNA's, however, RNA's do not always adopt global minimum structures. Rather, their structure is the result of the folding pathway followed by the structure in nature, which adopts sub-optimal folds occurring along the pathway. Our algorithm consists of an automaton that generates RNA structures by searching for optimal folding pathways. The automaton is endowed of operations to travel throughout the hyperspace of conformers embedded in a base pairing matrix. Using genetic programming it evolves optimizing its ability to find optimal pathways and finally 2D structures. Comparing the evolving automaton with conventional methods shows its potential.

Original language	English
Title of host publication	International Joint Conference on Neural Networks 2006, IJCNN '06
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2226-2233
Number of pages	8
ISBN (Print)	0780394909, 9780780394902
DOIs	https://doi.org/10.1109/ijcnn.2006.247018
Publication status	Published - 2006
Event	International Joint Conference on Neural Networks 2006, IJCNN '06 - Vancouver, BC, Canada Duration: Jul 16 2006 → Jul 21 2006

Publication series

Name	IEEE International Conference on Neural Networks - Conference Proceedings
ISSN (Print)	1098-7576

Other

Other	International Joint Conference on Neural Networks 2006, IJCNN '06
Country/Territory	Canada
City	Vancouver, BC
Period	7/16/06 → 7/21/06

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10.1109/ijcnn.2006.247018

Cite this

Del Carpio, C. A. M., Ismael, M., Ichiishi, E., Koyama, M., Kubo, M., & Miyamoto, A. (2006). An evolving automaton for RNA secondary structure prediction. In International Joint Conference on Neural Networks 2006, IJCNN '06 (pp. 2226-2233). [1716388] (IEEE International Conference on Neural Networks - Conference Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ijcnn.2006.247018

An evolving automaton for RNA secondary structure prediction. / Del Carpio, Carlos A.M.; Ismael, Mohamed; Ichiishi, Eichiro et al.

International Joint Conference on Neural Networks 2006, IJCNN '06. Institute of Electrical and Electronics Engineers Inc., 2006. p. 2226-2233 1716388 (IEEE International Conference on Neural Networks - Conference Proceedings).

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

Del Carpio, CAM, Ismael, M, Ichiishi, E, Koyama, M, Kubo, M & Miyamoto, A 2006, An evolving automaton for RNA secondary structure prediction. in International Joint Conference on Neural Networks 2006, IJCNN '06., 1716388, IEEE International Conference on Neural Networks - Conference Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 2226-2233, International Joint Conference on Neural Networks 2006, IJCNN '06, Vancouver, BC, Canada, 7/16/06. https://doi.org/10.1109/ijcnn.2006.247018

Del Carpio CAM, Ismael M, Ichiishi E, Koyama M, Kubo M, Miyamoto A. An evolving automaton for RNA secondary structure prediction. In International Joint Conference on Neural Networks 2006, IJCNN '06. Institute of Electrical and Electronics Engineers Inc. 2006. p. 2226-2233. 1716388. (IEEE International Conference on Neural Networks - Conference Proceedings). doi: 10.1109/ijcnn.2006.247018

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abstract = "Conventional methods for RNA 2D structure prediction search for minimal free energy structures. RNA's, however, RNA's do not always adopt global minimum structures. Rather, their structure is the result of the folding pathway followed by the structure in nature, which adopts sub-optimal folds occurring along the pathway. Our algorithm consists of an automaton that generates RNA structures by searching for optimal folding pathways. The automaton is endowed of operations to travel throughout the hyperspace of conformers embedded in a base pairing matrix. Using genetic programming it evolves optimizing its ability to find optimal pathways and finally 2D structures. Comparing the evolving automaton with conventional methods shows its potential.",

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AU - Miyamoto, Akira

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AB - Conventional methods for RNA 2D structure prediction search for minimal free energy structures. RNA's, however, RNA's do not always adopt global minimum structures. Rather, their structure is the result of the folding pathway followed by the structure in nature, which adopts sub-optimal folds occurring along the pathway. Our algorithm consists of an automaton that generates RNA structures by searching for optimal folding pathways. The automaton is endowed of operations to travel throughout the hyperspace of conformers embedded in a base pairing matrix. Using genetic programming it evolves optimizing its ability to find optimal pathways and finally 2D structures. Comparing the evolving automaton with conventional methods shows its potential.

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An evolving automaton for RNA secondary structure prediction

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