@article{biobayesnet2007,
author = {Nikolajewa, Swetlana and Pudimat, Rainer and Hiller, 
          Michael and Platzer, Matthias and Backofen, Rolf},
title = {{BioBayesNet}: a web server for feature extraction and 
         {Bayesian} network modeling of biological sequence data},
journal = {NAR},
year = {2007},
doi = {10.1093/nar/gkm292},
volume = {35},
user = {backofen},
pmid = {17537825},
pages = {W688-93},
number = {Web Server issue},
abstract = {BioBayesNet is a new web application that allows the easy 
            modeling and classification of biological data using 
            Bayesian networks. To learn Bayesian networks the user can 
            either upload a set of annotated FASTA sequences or a set of 
            pre-computed feature vectors. In case of FASTA sequences, 
            the server is able to generate a wide range of sequence and 
            structural features from the sequences. These features are 
            used to learn Bayesian networks. An automatic feature 
            selection procedure assists in selecting discriminative 
            features, providing an (locally) optimal set of features. 
            The output includes several quality measures of the overall 
            network and individual features as well as a graphical 
            representation of the network structure, which allows to 
            explore dependencies between features. Finally, the learned 
            Bayesian network or another uploaded network can be used to 
            classify new data. BioBayesNet facilitates the use of 
            Bayesian networks in biological sequences analysis and is 
            flexible to support modeling and classification applications 
            in various scientific fields. The BioBayesNet server is 
            available at 
            http://biwww3.informatik.uni-freiburg.de:8080/BioBayesNet/.}
}