Quantifying variances in comparative RNA secondary structure prediction.

ABSTRACT:

Background

With the advancement of next-generation sequencing and transcriptomics technologies, regulatory effects involving RNA, in particular RNA structural changes are being detected. These results often rely on RNA secondary structure predictions. However, current approaches to RNA secondary structure modelling produce predictions with a high variance in predictive accuracy, and we have little quantifiable knowledge about the reasons for these variances.

Results

In this paper we explore a number of factors which can contribute to poor RNA secondary structure prediction quality. We establish a quantified relationship between alignment quality and loss of accuracy. Furthermore, we define two new measures to quantify uncertainty in alignment-based structure predictions. One

SUBMITTER: Anderson JW 

PROVIDER: S-EPMC3667108 | biostudies-literature | 2013 May

REPOSITORIES: biostudies-literature