Publications
Our publications most relevant to our current research are:
R. Castelo and A. Roverato. Inference of regulatory networks from microarray data with R and the Bioconductor package qpgraph. In Next Generation Microarray Bioinformatics, J. Wang, A.C. Tan and T. Tian, Eds., pp. 215-233, Methods in Molecular Biology Series, Humana Press, USA, ISBN 978-1-61779-399-8,2012. [publisher, preprint, Bioconductor package].
I. Tur and R. Castelo. Learning mixed graphical models from data with p larger than n. In Proceedings 27th Conference on Uncertainty in Artificial Intelligence, F.G. Cozman and A. Pfeffer, Eds., pp. 689-697, AUAI Press, ISBN 978-0-9749039-7-2, Barcelona, 2011. [PDF].
B. Hartmann, R. Castelo, B. Miñana, E. Peden, M. Blanchette, D.C. Rio, R. Singh and J. Valcarcel. Distinct regulatory programs establish widespread sex-specific alternative splicing in Drosophila melanogaster. RNA, 17:453-468, 2011. [abstract].
R. Castelo and A. Roverato. Reverse engineering molecular regulatory networks from microarray data with qp-graphs, Journal of Computational Biology, 16(2):213-227, 2009. [preprint, supplement, Bioconductor package].
The ENCODE Project Consortium (including R. Castelo). Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project, Nature, 447:799-816, 2007. [abstract]
R. Castelo and A. Roverato. A robust procedure for Gaussian graphical model search from microarray data with p larger than n, Journal of Machine Learning Research, 7(Dec):2621-2650, 2006. [abstract and PDF, R package]
R. Castelo and R. Guigó. Splice Site Identification by idlBNs. Bioinformatics, 20(1):i69-i76, 2004. [abstract, supplementary information]
R. Castelo and T. Kocka. On inclusion-driven learning of Bayesian Networks. Journal of Machine Learning Research, 4(Sep):527-574, 2003. [abstract and PDF]