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Documentation

User Documentation

The Banjo User Guide explains how to use Banjo. It describes how to install and run Banjo, the parameters that the program requires, the names and formats of the data files that it uses, and how to put all the different pieces together to use Banjo flexibly with your own data.

Developer Documentation

The Banjo Developer Guide explains how to understand and modify Banjo source code. It is intended to be read after the Banjo User Guide and describes the design and architecture of the Banjo application. It also explains how to work with Banjo in the open source Eclipse development environment. The Eclipse IDE is available as a free download from http://www.eclipse.org.

Also, the Banjo code itself is documented internally. The internal documentation can be viewed online in standard JavaDoc format.

Research Papers

Our group has written a number of papers on Bayesian network inference, application of these methods to problems in systems biology, evaluation of these methods in a simulation framework, and extension and improvement of these methods for problems with small amounts of data. The experiments in the papers appearing before March 2005 were run before Banjo was first developed, but the Banjo codebase supersedes nearly all the code that we originally used in each paper. Relevant publications are:

  1. Smith, V., Yu, J., Smulders, T., Hartemink, A., & Jarvis, E. (2006) “Computational Inference of Neural Information Flow Networks.” PLoS Computational Biology, 2, November 2006. [Supp. Info.] [#1 Most Viewed Research Article at PLoS Computational Biology]
  2. Bernard, A. & Hartemink, A. (2006) “Evaluating Algorithms for Learning Biological Networks.” DREAM Workshop, September 2006.
  3. Hartemink, A. (2006) “Bayesian Networks and Informative Priors: Transcriptional Regulatory Network Models.” In Bayesian Inference for Gene Expression and Proteomics, Do, K.-A., Müller, P., & Vannucci, M., eds. Cambridge University Press: Cambridge, UK. pp. 401–424.
  4. Hartemink, A. (2005) “Reverse Engineering Gene Regulatory Networks.” Nature Biotechnology, 23, May 2005. pp. 554–555.
  5. Bernard, A. & Hartemink, A. (2005) “Informative Structure Priors: Joint Learning of Dynamic Regulatory Networks from Multiple Types of Data.” In Pacific Symposium on Biocomputing 2005 (PSB05), Altman, R., Dunker, A.K., Hunter, L., Jung, T., & Klein, T., eds. World Scientific: New Jersey. pp. 459–470. [Supp. Info.]
  6. Yu, J., Smith, V., Wang, P., Hartemink, A., & Jarvis, E. (2004) “Advances to Bayesian Network Inference for Generating Causal Networks from Observational Biological Data.” Bioinformatics, 20, December 2004. pp. 3594–3603.
  7. Smith, V., Jarvis, E., & Hartemink, A. (2003) “Influence of Topology and Data Collection on Functional Network Inference.” In Pacific Symposium on Biocomputing 2003 (PSB03), Altman, R., Dunker, A.K., Hunter, L., Jung, T., & Klein, T., eds. World Scientific: New Jersey. pp. 164–175.
  8. Yu, J., Smith, V., Wang, P., Hartemink, A., & Jarvis, E. (2002) “Using Bayesian Network Inference Algorithms to Recover Molecular Genetic Regulatory Networks.” International Conference on Systems Biology 2002 (ICSB02), December 2002.
  9. Jarvis, E., Smith, V., Wada, K., Rivas, M., McElroy, M., Smulders, T., Carninci, P., Hayashisaki, Y., Dietrich, F., Wu, X., McConnell, P., Yu, J., Wang, P., Hartemink, A., & Lin, S. (2002) “A Framework for Integrating the Songbird Brain.” Journal of Comparative Physiology A, 188, December 2002. pp. 961–980.
  10. Smith, V., Jarvis, E., & Hartemink, A. (2002) “Evaluating Functional Network Inference Using Simulations of Complex Biological Systems.” Intelligent Systems in Molecular Biology 2002 (ISMB02), Bioinformatics, 18:S1. pp. S216–S224.
  11. Hartemink, A., Gifford, D., Jaakkola, T., & Young, R. (2002) “Bayesian Methods for Elucidating Genetic Regulatory Networks.” IEEE Intelligent Systems, special issue on Intelligent Systems in Biology, 17, March/April 2002. pp. 37–43.
  12. Hartemink, A., Gifford, D., Jaakkola, T., & Young, R. (2002) “Combining Location and Expression Data for Principled Discovery of Genetic Regulatory Networks.” In Pacific Symposium on Biocomputing 2002 (PSB02), Altman, R., Dunker, A.K., Hunter, L., Lauderdale, K., & Klein, T., eds. World Scientific: New Jersey. pp. 437–449.
  13. Hartemink, A. (2001) “Principled Computational Methods for the Validation and Discovery of Genetic Regulatory Networks.” Massachusetts Institute of Technology, Ph.D. dissertation.
  14. Hartemink, A., Gifford, D., Jaakkola, T., & Young, R. (2001) “Using Graphical Models and Genomic Expression Data to Statistically Validate Models of Genetic Regulatory Networks.” In Pacific Symposium on Biocomputing 2001 (PSB01), Altman, R., Dunker, A.K., Hunter, L., Lauderdale, K., & Klein, T., eds. World Scientific: New Jersey. pp. 422–433.