BioBayesNet: A web server for feature extraction and Bayesian network modeling of biological sequence data

Nucleic Acids Research

Volumn 35, Issue SUPPL.2, 2007, Pages

  Nikolajewa, Swetlana ^a   Pudimat, Rainer ^b   Hiller, Michael ^b   Platzer, Matthias ^c   Backofen, Rolf ^b  

^a FRIEDRICH SCHILLER UNIVERSITY JENA   (Germany)

^b UNIVERSITY OF FREIBURG   (Germany)

^c FRITZ LIPMANN INSTITUTE   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

PROTEIN;

ALGORITHM; AMINO ACID SEQUENCE; ARTICLE; AUTOMATED PATTERN RECOGNITION; BAYES THEOREM; BIOLOGY; CHEMICAL STRUCTURE; CHEMISTRY; CLASSIFICATION; COMPUTER SIMULATION; INFORMATION RETRIEVAL; INTERNET; METHODOLOGY; MOLECULAR GENETICS; PROTEIN CONFORMATION; PROTEIN FOLDING; SEQUENCE ANALYSIS; STRUCTURE ACTIVITY RELATION;

ALGORITHMS; AMINO ACID SEQUENCE; BAYES THEOREM; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; INFORMATION STORAGE AND RETRIEVAL; INTERNET; MODELS, MOLECULAR; MOLECULAR SEQUENCE DATA; PATTERN RECOGNITION, AUTOMATED; PROTEIN CONFORMATION; PROTEIN FOLDING; PROTEINS; SEQUENCE ANALYSIS, PROTEIN; STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 34547569519     PISSN: 03051048     EISSN: 13624962     Source Type: Journal    
DOI: 10.1093/nar/gkm292     Document Type: Article

References (32)

1. Narlikar, L. and Hartemink, A.J. (2006) Sequence features of DNA binding sites reveal structural class of associated transcription factor. Bioinformatics, 22, 157-163.
2. Pudimat, R., Schukat-Talamazzini, E.G. and Backofen, R. (2005) A multiple-feature framework for modelling and predicting transcription factor binding sites. Bioinformatics, 21, 3082-3088.
3. Dror, G., Sorek, R. and Shamir, R. (2005) Accurate identification of alternatively spliced exons using support vector machine. Bioinformatics, 21, 897-901.
4. Hiller, M., Huse, K., Szafranski, K., Jahn, N., Hampe, J., Schreiber, S., Backofen, R. and Platzer, M. (2004) Widespread occurrence of alternative splicing at NAGNAG acceptors contributes to proteome plasticity. Nat. Genet., 36, 1255-1257.
5. Beaumont, M.A. and Rannala, B. (2004) The Bayesian revolution in genetics. Nat. Rev. Genet., 5, 251-261.
6. Needham, C.J., Bradford, J.R., Bulpitt, A.J. and Westhead, D.R. (2006) Inference in Bayesian networks. Nat. Biotechnol., 24, 51-53.
7. Chan, Z.S., Collins, L. and Kasabov, N. (2007) Bayesian learning of sparse gene regulatory networks. Biosystems, 87, 299-306.
8. Imoto, S., Higuchi, T., Goto, T., Tashiro, K., Kuhara, S. and Miyano, S. (2004) Combining microarrays and biological knowledge for estimating gene networks via bayesian networks. J. Bioinform. Comput. Biol., 2, 77-98.
9. Tamada, Y., Kim, S., Bannai, H., Imoto, S., Tashiro, K., Kuhara, S. and Miyano, S. (2003) Estimating gene networks from gene expression data by combining Bayesian network model with promoter element detection. Bioinformatics, 19(Suppl. 2), II227-II236.
10. Cai, Z., Tsung, E.F., Marinescu, V.D., Ramoni, M.F., Riva, A. and Kohane, I.S. (2004) Bayesian approach to discovering pathogenic SNPs in conserved protein domains. Hum. Mutat., 24, 178-184.
11. Green, M.L. and Karp, P.D. (2004) A Bayesian method for identifying missing enzymes in predicted metabolic pathway databases. BMC Bioinformatics, 5, 76.
12. Klingler, T.M. and Brutlag, D.L. (1994) Discovering structural correlations in alpha-helices. Protein Sci., 3, 1847-1857.
13. Needham, C.J., Bradford, J.R., Bulpitt, A.J., Care, M.A. and Westhead, D.R. (2006) Predicting the effect of missense mutations on protein function: analysis with Bayesian networks. BMC Bioinformatics, 7, 405.
14. Barash, Y., Kaplan, T., Friedman, N. and Elidan, G. (2003), Proceedings of the 7th International Conference on Research in Computational Molecular Biology (RECOMB), Berlin, pp. 28-37.
15. Cai, D., Delcher, A., Kao, B. and Kasif, S. (2000) Modeling splice sites with Bayes networks. Bioinformatics, 16, 152-158.
16. Chen, T.M., Lu, C.C. and Li, W.H. (2005) Prediction of splice sites with dependency graphs and their expanded bayesian networks. Bioinformatics, 21, 471-482.
17. Deforche, K., Silander, T., Camacho, R., Grossman, Z., Soares, M.A., Van Laethem, K., Kantor, R., Moreau, Y. and Vandamme, A.M. (2006) Analysis of HIV-1 pol sequences using Bayesian Networks: implications for drug resistance. Bioinformatics, 22, 2975-2979.
18. Eddy, S.R. (1998) Profile hidden Markov models. Bioinformatics, 14, 755-763.
19. Bateman, A., Birney, E., Cerruti, L., Durbin, R., Etwiller, L., Eddy, S.R., Griffiths-Jones, S., Howe, K.L., Marshall, M. et al. (2002) The Pfam protein families database. Nucleic Acids Res., 30, 276-280.
20. Bradford, J.R., Needham, C.J., Bulpitt, A.J. and Westtshead, D.R. (2006) Insights into protein-protein interfaces using a Bayesian network prediction method. Journal of Molecular Biology, 362, 365-86.
21. Pudil, P., Novovicova, J. and Kittler, J. (1994) Floating search methods in feature-selection. Pattern. Recog. Lett., 15, 1119-1125.
22. Friedman, N., Geiger, D. and Goldszmidt, M. (1997) Bayesian network classifiers. Machine Learn., 29, 131-163.
23. Chow, C.K. and Liu, C.N. (1968) Approximating discrete probability distributions with dependence trees. IEEE Transaction on Information Theory, 14, 462-467.
24. Jensen, F.V. (2001) Bayesian Networks and Decision Graphs Springer, Berlin
25. el Hassan, M.A. and Calladine, C.R. (1995) The assessment of the geometry of dinucleotide steps in double-helical DNA; a new local calculation scheme. J. Mol. Biol., 251, 648-664.
26. Ponomarenko, J.V., Ponomarenko, M.P., Frolov, A.S., Vorobyev, D.G., Overton, G.C. and Kolchanov, N.A. (1999) Conformational and physicochemical DNA features specific for transcription factor binding sites. Bioinformatics, 15, 654-668.
27. Muckstein, U., Tafer, H., Hackermuller, J., Bernhart, S.H., Stadler, P.F. and Hofacker, I.L. (2006) Thermodynamics of RNA-RNA binding. Bioinformatics, 22, 1177-1182.
28. Fayyad, U.M. and Irani, K.B. (1993) Multi-interval discretization of continuousvalued attributes for classification learning. IJCAI, 2, 1022-1027.
29. Quinlan, J.R. (1993) Programs for Machine Learning Morgan Kaufmann, San Mateo.
30. Cozman, F.G. (2000) Generalizing variable elimination in Bayesian networks. In Proceedings of Workshop on Probabilistic Reasoning in Artificial Intelligence, pp. 1-6.
31. Pocock, M., Down, T. and Hubbard, T. (2000) BioJava: open source components for bioinformatics. SIGBIO Newsletter, 20, 10-12.
32. Sacha, J.P., Goodenday, L.S. and Cios, K.J. (2002) Bayesian learning for cardiac SPECT image interpretation. Artif. Intell. Med., 26, 109-143.