Joint modeling of DNA sequence and physical properties to improve eukaryotic promoter recognition.

Journal Article (Journal Article)

We present an approach to integrate physical properties of DNA, such as DNA bendability or GC content, into our probabilistic promoter recognition system McPROMOTER. In the new model, a promoter is represented as a sequence of consecutive segments represented by joint likelihoods for DNA sequence and profiles of physical properties. Sequence likelihoods are modeled with interpolated Markov chains, physical properties with Gaussian distributions. The background uses two joint sequence/profile models for coding and non-coding sequences, each consisting of a mixture of a sense and an anti-sense submodel. On a large Drosophila test set, we achieved a reduction of about 30% of false positives when compared with a model solely based on sequence likelihoods.

Full Text

Duke Authors

Cited Authors

  • Ohler, U; Niemann, H; Liao Gc, ; Rubin, GM

Published Date

  • 2001

Published In

Volume / Issue

  • 17 Suppl 1 /

Start / End Page

  • S199 - S206

PubMed ID

  • 11473010

Pubmed Central ID

  • 11473010

International Standard Serial Number (ISSN)

  • 1367-4803

Digital Object Identifier (DOI)

  • 10.1093/bioinformatics/17.suppl_1.s199


  • eng

Conference Location

  • England