Statistical and Machine Learning Approaches for Network Analysis

References

1. F. Emmert-Streib, M. Dehmer. Networks for systems biology: conceptual connection of data and function. IET Syst. Biol. 5, 185–207 (2011).

2. F. Emmert-Streib, G.V. Glazko. Network biology: a direct approach to study biological function. Wiley Interdiscip. Rev. Syst. Biol. Med. 3, 379-3-91 (2011).

3. G. Stolovitzky, A. Califano (ed.) Reverse Engineering Biological Networks: Opportunities and Challenges in Computational Methods for Pathway Inference. Wiley-Blackwell, 2007.

4. G. Stolovitzky, R.J. Prill, A. Califano. Lessons from the DREAM 2 Challenges. Ann. N. Y. Acad. Sci. 1158, 159–195 (2009).

5. M. Schena (ed.) Protein Microarrays. Jones and Bartlett Publishers, 2004.

6. S. Sechi, (ed.) Quantitative Proteomics by Mass Spectrometry. Humana Press, 2007.

7. P. Collas, J.A. Dahl. Chop it, ChIP it, check it: the current status of chromatin immunoprecipitation. Front Biosci. 13, 929–943 (2008).

8. R. Edgar, M. Domrachev, A.E. Lash. Gene expression omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 30, 207–210 (2002).

9. P.R. Rosenbaum. Observational Studies, Springer, New York, 2002.

10. R. Rubin. Estimating causal effects of treatments in randomized and nonrandomized studies. J. Educ. Psychol. 66, 688–701 (1974).

11. J.J. Faith, B. Hayete, J.T. Thaden, I. Mogno, J. Wierzbowski, G. Cottarel, S. Kasif, J.J. Collins, T.S. Gardner. Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of ...