Promoter prediction in E. coli based on SIDD profiles and Artificial Neural Networks.

ABSTRACT:

Background

One of the major challenges in biology is the correct identification of promoter regions. Computational methods based on motif searching have been the traditional approach taken. Recent studies have shown that DNA structural properties, such as curvature, stacking energy, and stress-induced duplex destabilization (SIDD) are useful in promoter prediction, as well. In this paper, the currently used SIDD energy threshold method is compared to the proposed artificial neural network (ANN) approach for finding promoters based on SIDD profile data.

Results

When compared to the SIDD threshold prediction method, artificial neural networks showed noticeable improvements for precision, recall, and F-score over a range of values. The maximal F-score for the ANN classifier was

SUBMITTER: Bland C 

PROVIDER: S-EPMC3026364 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature