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REFERENCES

Published online by Cambridge University Press:  05 June 2012

Pavel Pevzner
Affiliation:
University of California, San Diego
Ron Shamir
Affiliation:
Tel-Aviv University
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Publisher: Cambridge University Press
Print publication year: 2011

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References

[1] N., Guelzim, S., Bottani, P., Bourgine, and F., Képès. Topological and causal structure of the yeast transcriptional regulatory network. Nature Genet., 31:60–63, 2002.Google Scholar
[2] National Human Genome Research Institute. Image provided for free public use through the US National Institutes of Health Image Bank as NHGRI press gallery photo 20018.
[3] M. B., Eisen, P. T., Spellman, P. O., Brown, and D., Botstein. Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. U S A, 95:14, 863–14, 868, 1998.Google Scholar
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[8] A., Zhang. Advanced Analysis of Gene Expression Microarray Data. World Scientific Publishing, Toh Tuck Link, Singapore, 2006.
[9] L., Wasserman. All of Statistics. Springer, New York, 2004.
[10] L., Wasserman. All of Non-Parametric Statistics. Springer, New York, 2006.
[11] T. M., Mitchell. Machine Learning. WCB/McGraw-Hill, Boston, MA, 1997.
[12] T., Hastie, R., Tibshirani, and J., Friedman. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer-Verlag, New York, 2001.
[13] P., Congdon. Applied Bayesian Modelling. John Wiley and Sons, Chichester, 2003.
[14] A., Gelman, J. B., Carlin, H. S., Stern, and D. B., Rubin. Bayesian Data Analysis. CRC Press, Boca Raton, FL, 2004.
[15] R. E., Neapolitan. Learning Bayesian Networks. Pearson Prentice Hall, Upper Saddle River, NJ, 2004.
[16] W. R., Gilks, S., Richardson, and D. J., Spiegelhalter. Markov Chain Monte Carlo in Practice. Chapman and Hall/CRC, Boca Raton, FL, 1996.
[17] A., Ruszczyński. Nonlinear Optimization. Princeton University Press, Princeton, NJ, 2006.
[18] S., Boyd and L., Vandenberghe. Convex Optimization. Cambridge University Press, New York, 2004.
[19] P., Dhaseleer, S., Liang, and R., Somogyi. Genetic network inference: From co-expression clustering to reverse engineering. Bioinformatics, 16:707–726, 2000.Google Scholar
[20] N., Friedman, M., Linial, I., Nachman, and D., Pe'er. Using Bayesian networks to analyze expression data. J. Comp. Biol., 7:601–620, 2000.Google Scholar

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  • REFERENCES
  • Edited by Pavel Pevzner, University of California, San Diego, Ron Shamir, Tel-Aviv University
  • Book: Bioinformatics for Biologists
  • Online publication: 05 June 2012
  • Chapter DOI: https://doi.org/10.1017/CBO9780511984570.019
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  • REFERENCES
  • Edited by Pavel Pevzner, University of California, San Diego, Ron Shamir, Tel-Aviv University
  • Book: Bioinformatics for Biologists
  • Online publication: 05 June 2012
  • Chapter DOI: https://doi.org/10.1017/CBO9780511984570.019
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • REFERENCES
  • Edited by Pavel Pevzner, University of California, San Diego, Ron Shamir, Tel-Aviv University
  • Book: Bioinformatics for Biologists
  • Online publication: 05 June 2012
  • Chapter DOI: https://doi.org/10.1017/CBO9780511984570.019
Available formats
×