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A parallel evolutionary algorithm for RNA secondary structure prediction using stacking-energies (INN and INN-HB)

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3 Author(s)
Hendriks, A. ; Simon Fraser Univ., Burnaby, BC, Canada ; Deschenes, A. ; Wiese, K.C.

This work presents a coarse-grained distributed genetic algorithm (GA) for RNA secondary structure prediction. This research builds on previous work and contains two new thermodynamic models, INN and INN-HB, which add stacking-energies using base pair adjacencies. Comparison tests were performed against the original serial GA on known structures that are 122, 543, and 784 nucleotides in length on a wide variety of parameter settings. The effects of the new models are investigated, the predicted structures are compared to known structures and the GA is compared against a serial GA with identical models. Both algorithms perform well and are able to predict structures with high accuracy for short sequences.

Published in:

Computational Intelligence in Bioinformatics and Computational Biology, 2004. CIBCB '04. Proceedings of the 2004 IEEE Symposium on

Date of Conference:

7-8 Oct. 2004