@inproceedings{pudimat:2004:gcb,
author = {Pudimat, Rainer and Schukat-Talamazzini, E. G. and Backofen, Rolf},
title = {Feature Based Representation and Detection of 
         Transcription Factor Binding Sites},
booktitle = {GCB},
year = {2004},
doi = {https://dl.gi.de/items/eb65bef4-acb7-4551-a9bc-5bc162d14ecf},
volume = {53},
user = {rpudimat},
series = {LNI},
publists = {All and Rainer Pudimat and Rolf Backofen},
publisher = {GI},
pages = {43-52},
keywords = {Bayesian networks, transcription factor binding sites, 
            stochastic modelling, gene expression},
editor = {Robert Giegerich and
          Jens Stoye},
abstract = {
            The prediction of transcription factor binding sites is an important
            problem, since it reveals information about the transcriptional regulation
            of genes. A commonly used representation of these sites are position
            specific weight matrices which show weak predictive power.
            We introduce a feature-based modelling approach, which is able to deal with
            various kind of biological properties of binding sites and models them
            via em Bayesian belief networks. The presented results imply higher
            model accuracy in contrast to the PSSM approach.}
}