RGRNA: prediction of RNA secondary structure based on replacement and growth of stems

Jin Li, Chengzhen Xu, Hong Liang, Wang Cong, Ying Wang, Kuan Luan, Yunlong Liu

Research output: Contribution to journalArticle

Abstract

Owing to their structural diversity, RNAs perform many diverse biological functions in the cell. RNA secondary structure is thus important for predicting RNA function. Here, we propose a new combinatorial optimization algorithm, named RGRNA, to improve the accuracy of predicting RNA secondary structure. Following the establishment of a stempool, the stems are sorted by length, and chosen from largest to smallest. If the stem selected is the true stem, the secondary structure of this stem when combined with another stem selected at random will have low free energy, and the free energy will tend to gradually diminish. The free energy is considered as a parameter and the structure is converted into binary numbers to determine stem compatibility, for step-by-step prediction of the secondary structure for all combinations of stems. The RNA secondary structure can be predicted by the RGRNA method. Our experimental results show that the proposed algorithm outperforms RNAfold in terms of sensitivity, specificity, and Matthews correlation coefficient value.

Original languageEnglish (US)
Pages (from-to)1261-1272
Number of pages12
JournalComputer Methods in Biomechanics and Biomedical Engineering
Volume20
Issue number12
DOIs
StatePublished - Sep 10 2017

Fingerprint

RNA
Free energy
Combinatorial optimization

Keywords

  • heuristic algorithms
  • prediction
  • RGRNA method
  • RNA secondary structure
  • stempool

ASJC Scopus subject areas

  • Bioengineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Computer Science Applications

Cite this

RGRNA : prediction of RNA secondary structure based on replacement and growth of stems. / Li, Jin; Xu, Chengzhen; Liang, Hong; Cong, Wang; Wang, Ying; Luan, Kuan; Liu, Yunlong.

In: Computer Methods in Biomechanics and Biomedical Engineering, Vol. 20, No. 12, 10.09.2017, p. 1261-1272.

Research output: Contribution to journalArticle

Li, Jin ; Xu, Chengzhen ; Liang, Hong ; Cong, Wang ; Wang, Ying ; Luan, Kuan ; Liu, Yunlong. / RGRNA : prediction of RNA secondary structure based on replacement and growth of stems. In: Computer Methods in Biomechanics and Biomedical Engineering. 2017 ; Vol. 20, No. 12. pp. 1261-1272.
@article{f36d1a75e500400eb250c175cc495a0d,
title = "RGRNA: prediction of RNA secondary structure based on replacement and growth of stems",
abstract = "Owing to their structural diversity, RNAs perform many diverse biological functions in the cell. RNA secondary structure is thus important for predicting RNA function. Here, we propose a new combinatorial optimization algorithm, named RGRNA, to improve the accuracy of predicting RNA secondary structure. Following the establishment of a stempool, the stems are sorted by length, and chosen from largest to smallest. If the stem selected is the true stem, the secondary structure of this stem when combined with another stem selected at random will have low free energy, and the free energy will tend to gradually diminish. The free energy is considered as a parameter and the structure is converted into binary numbers to determine stem compatibility, for step-by-step prediction of the secondary structure for all combinations of stems. The RNA secondary structure can be predicted by the RGRNA method. Our experimental results show that the proposed algorithm outperforms RNAfold in terms of sensitivity, specificity, and Matthews correlation coefficient value.",
keywords = "heuristic algorithms, prediction, RGRNA method, RNA secondary structure, stempool",
author = "Jin Li and Chengzhen Xu and Hong Liang and Wang Cong and Ying Wang and Kuan Luan and Yunlong Liu",
year = "2017",
month = "9",
day = "10",
doi = "10.1080/10255842.2017.1340460",
language = "English (US)",
volume = "20",
pages = "1261--1272",
journal = "Computer Methods in Biomechanics and Biomedical Engineering",
issn = "1025-5842",
publisher = "Informa Healthcare",
number = "12",

}

TY - JOUR

T1 - RGRNA

T2 - prediction of RNA secondary structure based on replacement and growth of stems

AU - Li, Jin

AU - Xu, Chengzhen

AU - Liang, Hong

AU - Cong, Wang

AU - Wang, Ying

AU - Luan, Kuan

AU - Liu, Yunlong

PY - 2017/9/10

Y1 - 2017/9/10

N2 - Owing to their structural diversity, RNAs perform many diverse biological functions in the cell. RNA secondary structure is thus important for predicting RNA function. Here, we propose a new combinatorial optimization algorithm, named RGRNA, to improve the accuracy of predicting RNA secondary structure. Following the establishment of a stempool, the stems are sorted by length, and chosen from largest to smallest. If the stem selected is the true stem, the secondary structure of this stem when combined with another stem selected at random will have low free energy, and the free energy will tend to gradually diminish. The free energy is considered as a parameter and the structure is converted into binary numbers to determine stem compatibility, for step-by-step prediction of the secondary structure for all combinations of stems. The RNA secondary structure can be predicted by the RGRNA method. Our experimental results show that the proposed algorithm outperforms RNAfold in terms of sensitivity, specificity, and Matthews correlation coefficient value.

AB - Owing to their structural diversity, RNAs perform many diverse biological functions in the cell. RNA secondary structure is thus important for predicting RNA function. Here, we propose a new combinatorial optimization algorithm, named RGRNA, to improve the accuracy of predicting RNA secondary structure. Following the establishment of a stempool, the stems are sorted by length, and chosen from largest to smallest. If the stem selected is the true stem, the secondary structure of this stem when combined with another stem selected at random will have low free energy, and the free energy will tend to gradually diminish. The free energy is considered as a parameter and the structure is converted into binary numbers to determine stem compatibility, for step-by-step prediction of the secondary structure for all combinations of stems. The RNA secondary structure can be predicted by the RGRNA method. Our experimental results show that the proposed algorithm outperforms RNAfold in terms of sensitivity, specificity, and Matthews correlation coefficient value.

KW - heuristic algorithms

KW - prediction

KW - RGRNA method

KW - RNA secondary structure

KW - stempool

UR - http://www.scopus.com/inward/record.url?scp=85025449759&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85025449759&partnerID=8YFLogxK

U2 - 10.1080/10255842.2017.1340460

DO - 10.1080/10255842.2017.1340460

M3 - Article

C2 - 28730879

AN - SCOPUS:85025449759

VL - 20

SP - 1261

EP - 1272

JO - Computer Methods in Biomechanics and Biomedical Engineering

JF - Computer Methods in Biomechanics and Biomedical Engineering

SN - 1025-5842

IS - 12

ER -