title: BioBayesNet: a web server for feature extraction and Bayesian network modeling of biological sequence data.
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/.
authors.affiliation: Department of Bioinformatics, Friedrich-Schiller-University Jena, Ernst-Abbe-Platz 2, 07743 Jena, Germany.
authors.forename: Swetlana
authors.initials: S
authors.lastname: Nikolajewa
authors.forename: Rainer
authors.initials: R
authors.lastname: Pudimat
authors.forename: Michael
authors.initials: M
authors.lastname: Hiller
authors.forename: Matthias
authors.initials: M
authors.lastname: Platzer
authors.forename: Rolf
authors.initials: R
authors.lastname: Backofen
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D001499:Bayes Theorem; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D016247:Information Storage and Retrieval; D020407:Internet; D008958:Models, Molecular; D008969:Molecular Sequence Data; D010363:Pattern Recognition, Automated / Q000379:methods*; D011487:Protein Conformation; D017510:Protein Folding; D011506:Proteins / Q000032:analysis* / Q000737:chemistry* / Q000145:classification; D020539:Sequence Analysis, Protein / Q000379:methods*; D013329:Structure-Activity Relationship
chemical_list: D011506:Proteins