### Abstract

Motivation: The importance of accurate and fast predictions of multiple alignments for RNA sequences has increased due to recent findings about functional non-coding RNAs. Recent studies suggest that maximizing the expected accuracy of predictions will be useful for many problems in bioinformatics.Results: We designed a novel estimator for multiple alignments of structured RNAs, based on maximizing the expected accuracy of predictions. First, we define the maximum expected accuracy (MEA) estimator for pairwise alignment of RNA sequences. This maximizes the expected sum-of-pairs score (SPS) of a predicted alignment under a probability distribution of alignments given by marginalizing the Sankoff model. Then, by approximating the MEA estimator, we obtain an estimator whose time complexity is O(L^{3}+c^{2}dL^{2}) where L is the length of input sequences and both c and d are constants independent of L. The proposed estimator can handle uncertainty of secondary structures and alignments that are obstacles in Bioinformatics because it considers all the secondary structures and all the pairwise alignments as input sequences. Moreover, we integrate the probabilistic consistency transformation (PCT) on alignments into the proposed estimator. Computational experiments using six benchmark datasets indicate that the proposed method achieved a favorable SPS and was the fastest of many state-of-the-art tools for multiple alignments of structured RNAs.

Original language | English |
---|---|

Article number | btp580 |

Pages (from-to) | 3236-3243 |

Number of pages | 8 |

Journal | Bioinformatics |

Volume | 25 |

Issue number | 24 |

DOIs | |

Publication status | Published - 2009 Oct 6 |

Externally published | Yes |

### Fingerprint

### ASJC Scopus subject areas

- Biochemistry
- Molecular Biology
- Computational Theory and Mathematics
- Computer Science Applications
- Computational Mathematics
- Statistics and Probability
- Medicine(all)

### Cite this

*Bioinformatics*,

*25*(24), 3236-3243. [btp580]. https://doi.org/10.1093/bioinformatics/btp580

**CentroidAlign : Fast and accurate aligner for structured RNAs by maximizing expected sum-of-pairs score.** / Hamada, Michiaki; Sato, Kengo; Kiryu, Hisanori; Mituyama, Toutai; Asai, Kiyoshi.

Research output: Contribution to journal › Article

*Bioinformatics*, vol. 25, no. 24, btp580, pp. 3236-3243. https://doi.org/10.1093/bioinformatics/btp580

}

TY - JOUR

T1 - CentroidAlign

T2 - Fast and accurate aligner for structured RNAs by maximizing expected sum-of-pairs score

AU - Hamada, Michiaki

AU - Sato, Kengo

AU - Kiryu, Hisanori

AU - Mituyama, Toutai

AU - Asai, Kiyoshi

PY - 2009/10/6

Y1 - 2009/10/6

N2 - Motivation: The importance of accurate and fast predictions of multiple alignments for RNA sequences has increased due to recent findings about functional non-coding RNAs. Recent studies suggest that maximizing the expected accuracy of predictions will be useful for many problems in bioinformatics.Results: We designed a novel estimator for multiple alignments of structured RNAs, based on maximizing the expected accuracy of predictions. First, we define the maximum expected accuracy (MEA) estimator for pairwise alignment of RNA sequences. This maximizes the expected sum-of-pairs score (SPS) of a predicted alignment under a probability distribution of alignments given by marginalizing the Sankoff model. Then, by approximating the MEA estimator, we obtain an estimator whose time complexity is O(L3+c2dL2) where L is the length of input sequences and both c and d are constants independent of L. The proposed estimator can handle uncertainty of secondary structures and alignments that are obstacles in Bioinformatics because it considers all the secondary structures and all the pairwise alignments as input sequences. Moreover, we integrate the probabilistic consistency transformation (PCT) on alignments into the proposed estimator. Computational experiments using six benchmark datasets indicate that the proposed method achieved a favorable SPS and was the fastest of many state-of-the-art tools for multiple alignments of structured RNAs.

AB - Motivation: The importance of accurate and fast predictions of multiple alignments for RNA sequences has increased due to recent findings about functional non-coding RNAs. Recent studies suggest that maximizing the expected accuracy of predictions will be useful for many problems in bioinformatics.Results: We designed a novel estimator for multiple alignments of structured RNAs, based on maximizing the expected accuracy of predictions. First, we define the maximum expected accuracy (MEA) estimator for pairwise alignment of RNA sequences. This maximizes the expected sum-of-pairs score (SPS) of a predicted alignment under a probability distribution of alignments given by marginalizing the Sankoff model. Then, by approximating the MEA estimator, we obtain an estimator whose time complexity is O(L3+c2dL2) where L is the length of input sequences and both c and d are constants independent of L. The proposed estimator can handle uncertainty of secondary structures and alignments that are obstacles in Bioinformatics because it considers all the secondary structures and all the pairwise alignments as input sequences. Moreover, we integrate the probabilistic consistency transformation (PCT) on alignments into the proposed estimator. Computational experiments using six benchmark datasets indicate that the proposed method achieved a favorable SPS and was the fastest of many state-of-the-art tools for multiple alignments of structured RNAs.

UR - http://www.scopus.com/inward/record.url?scp=75849160582&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=75849160582&partnerID=8YFLogxK

U2 - 10.1093/bioinformatics/btp580

DO - 10.1093/bioinformatics/btp580

M3 - Article

C2 - 19808876

AN - SCOPUS:75849160582

VL - 25

SP - 3236

EP - 3243

JO - Bioinformatics

JF - Bioinformatics

SN - 1367-4803

IS - 24

M1 - btp580

ER -