Inferring interaction networks using the IBP applied to microRNA target prediction

Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011

Volumn , Issue , 2011, Pages

  Le, Hai Son ^a   Bar Joseph, Ziv ^a  

^a Carnegie Mellon University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

RNA;

CLUSTERINGS; IN NETWORKS; INTERACTION NETWORKS; MICRORNA TARGET PREDICTIONS; NETWORK DATA; NON-PARAMETRIC BAYESIAN MODELING; PROPERTY; SYNTHETIC AND REAL DATA;

BAYESIAN NETWORKS;

EID: 85162507177     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. E.M. Airoldi, D.M. Blei, S.E. Fienberg, and E.P. Xing. Mixed membership stochastic blockmodels. The Journal of Machine Learning Research, 9:1981-2014, 2008.
2. Z. Bar-Joseph, G.K. Gerber, T.I. Lee, et al. Computational discovery of gene modules and regulatory networks. Nature biotechnology, 21(11):1337-1342, 2003.
3. T. Beißbarth and T.P. Speed. GOstat: find statistically overrepresented Gene Ontologies within a group of genes. Bioinformatics, 20(9):1464, 2004.
4. David M. Blei and Peter Frazier. Distance dependent chinese restaurant processes. In Johannes Frnkranz and Thorsten Joachims, editors, ICML, pages 87-94. Omnipress, 2010.
5. S. Chib and E. Greenberg. Understanding the metropolis-hastings algorithm. Amer. Statistician, 49(4):327-335, 1995.
6. J. Dong, G. Jiang, Y.W. Asmann, S. Tomaszek, et al. MicroRNA Networks in Mouse Lung Organogenesis. PloS one, 5(5):4645-4652, 2010.
7. T. Griffiths and Z. Ghahramani. Infinite latent feature models and the Indian buffet process. In Advances in Neural Information Processing Systems, 18:475, 2006.
8. J.C. Huang, T. Babak, T.W. Corson, et al. Using expression profiling data to identify human microRNA targets. Nature methods, 4(12):1045-1049, 2007.
9. C. Kemp, J.B. Tenenbaum, T.L. Griffiths, et al. Learning systems of concepts with an infinite relational model. In Proc. 21st Natl Conf. Artif. Intell.(1), page 381, 2006.
10. E. Meeds, Z. Ghahramani, R.M. Neal, and S.T. Roweis. Modeling dyadic data with binary latent factors. In Advances in NIPS, 19:977, 2007.
11. K.T. Miller, T.L. Griffiths, and M.I. Jordan. The phylogenetic indian buffet process: A nonexchangeable nonparametric prior for latent features. In UAI, 2008.
12. K.T. Miller, T.L. Griffiths, and M.I. Jordan. Nonparametric latent feature models for link prediction. In Advances in Neural Information Processing Systems, 2009.
13. P. Orbanz and J.M. Buhmann. Nonparametric bayesian image segmentation. International Journal of Computer Vision, 77(1):25-45, 2008.
14. ME Peter. Targeting of mrnas by multiple mirnas: the next step. Oncogene, 29(15):2161-2164, 2010.
15. N. Rajewsky. microRNA target predictions in animals. Nature genetics, 38:S8-S13, 2006.
16. P. Shannon, A. Markiel, O. Ozier, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome research, 13(11):2498, 2003.
17. F. Stingo, Y. Chen, M. Vannucci, et al. A Bayesian graphical modeling approach to microRNA regulatory network inference. Ann. Appl. Statist, 2010.
18. A. Ventura, A.G. Young, M.M. Winslow, et al. Targeted Deletion Reveals Essential and Overlapping Functions of the miR-17-92 Family of miRNA Clusters. Cell, 132:875-886, 2008.
19. Y.J. Wang and G.Y. Wong. Stochastic blockmodels for directed graphs. Journal of the American Statistical Association, 82(397):8-19, 1987.
20. C. Xiao and K. Rajewsky. MicroRNA control in the immune system: basic principles. Cell, 136(1):26-36, 2009.