Predicting consensus structures for RNA alignments via pseudo-energy minimization

Junilda Spirollari, Jason T.L. Wang, Kaizhong Zhang, Vivian Bellofatto, Yongkyu Park, Bruce A. Shapiro

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Thermodynamic processes with free energy parameters are often used in algorithms that solve the free energy minimization problem to predict secondary structures of single RNA sequences. While results from these algorithms are promising, an observation is that single sequence-based methods have moderate accuracy and more information is needed to improve on RNA secondary structure prediction, such as covariance scores obtained from multiple sequence alignments. We present in this paper a new approach to predicting the consensus secondary structure of a set of aligned RNA sequences via pseudo-energy minimization. Our tool, called RSpredict, takes into account sequence covariation and employs effective heuristics for accuracy improvement. RSpredict accepts, as input data, a multiple sequence alignment in FASTA or ClustalW format and outputs the consensus secondary structure of the input sequences in both the Vienna style Dot Bracket format and the Connectivity Table format. Our method was compared with some widely used tools including KNetFold, Pfold and RNAalifold. A comprehensive test on different datasets including Rfam sequence alignments and a multiple sequence alignment obtained from our study on the Drosophila X chromosome reveals that RSpredict is competitive with the existing tools on the tested datasets. RSpredict is freely available online as a web server and also as a jar file for download at http://datalab.njit.edu/biology/RSpredict.

Original languageEnglish (US)
Pages (from-to)51-69
Number of pages19
JournalBioinformatics and Biology Insights
Volume2009
Issue number3
DOIs
StatePublished - 2009

All Science Journal Classification (ASJC) codes

  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Mathematics
  • Applied Mathematics

Keywords

  • Drosophila secondary structure
  • Normalized energy
  • RNA secondary structure prediction
  • Rfam sequence alignments

Fingerprint Dive into the research topics of 'Predicting consensus structures for RNA alignments via pseudo-energy minimization'. Together they form a unique fingerprint.

Cite this