Direct updating of an RNA base-pairing probability matrix with marginal probability constraints

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

A base-pairing probability matrix (BPPM) stores the probabilities for every possible base pair in an RNA sequence and has been used in many algorithms in RNA informatics (e.g., RNA secondary structure prediction and motif search). In this study, we propose a novel algorithm to perform iterative updates of a given BPPM, satisfying marginal probability constraints that are (approximately) given by recently developed biochemical experiments, such as SHAPE, PAR, and FragSeq. The method is easily implemented and is applicable to common models for RNA secondary structures, such as energy-based or machine-learning-based models. In this article, we focus mainly on the details of the algorithms, although preliminary computational experiments will also be presented.

Original languageEnglish
Pages (from-to)1265-1276
Number of pages12
JournalJournal of Computational Biology
Volume19
Issue number12
DOIs
Publication statusPublished - 2012 Dec 1
Externally publishedYes

Fingerprint

RNA
Pairing
Base Pairing
Updating
RNA Secondary Structure
Informatics
Structure Prediction
Computational Experiments
Learning systems
Machine Learning
Update
Experiments
Energy
Model
Experiment

Keywords

  • algorithms
  • alignment
  • RNA
  • secondary structure
  • sequence analysis

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics
  • Computational Mathematics
  • Modelling and Simulation
  • Computational Theory and Mathematics

Cite this

Direct updating of an RNA base-pairing probability matrix with marginal probability constraints. / Hamada, Michiaki.

In: Journal of Computational Biology, Vol. 19, No. 12, 01.12.2012, p. 1265-1276.

Research output: Contribution to journalArticle

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