 |
Marco Scutari, Ph.D. Contact Information Here is my curriculum vitae. |
Publications
Books
- Graphical Models in R (tentative title).
R. Nagarajan, M. Scutari and S. Lèbre (in preparation, not to be confused with Søren Højsgaard, David Edwards and Steffen Lauritzen book).
Springer.
Book Chapters
|
|
Refereed Journal Articles
- Functional Relationships Between Genes Associated with Differentiation Potential of Aged Myogenic Progenitors.
[ html |
pdf ]
R. Nagarajan, S. Datta, M. Scutari, M. L. Beggs, G. T. Nolen and C. A. Peterson (2010).
Frontiers in Physiology (Systems Biology section), 1(21), 1–8. - Learning Bayesian Networks with the bnlearn R Package.
[ arXiv (preprint) |
html |
pdf ]
M. Scutari (2010).
Journal of Statistical Software, 35(3), 1–22.
Refereed Conference Proceedings
- On Identifying Significant Edges in Graphical Models.
[ arXiv |
proceedings ]
M. Scutari and R. Nagarajan (2012, submitted).
Artificial Intelligence in Medicine. Special Issue containing selected papers from the Workshop “Probabilistic Problem Solving in Biomedicine, 13th Conference on Artificial Intelligence in Medicine (AIME'11)”, Bled (Slovenia), July 2, 2011. - Bayesian Network Structure Learning with Permutation Tests.
[ arXiv (preprint) ]
M. Scutari and A. Brogini (2012, in print).
Communications in Statistics – Theory & Methods. Special Issue containing the Proceedings of the Conference “Statistics for Complex Problems: the Multivariate Permutation Approach and Related Topics”, Padova (Italy), June 14–15, 2010. - NATbox: a Network Analysis Toolbox in R.
[ html |
pdf ]
S. S. Chavan, M. A. Bauer, M. Scutari and R. Nagarajan (2009).
BMC Bioinformatics, 10(Suppl 11):S14. Supplement containing the Proceedings of the 6th Annual MCBIOS Conference (Transformational Bioinformatics: Delivering Value from Genomes), Starkville (MS, USA), February 20–21, 2009.
Ph.D. Thesis
- Measures of Variability for Graphical Models.
[ pdf (final + fixes) ]
Marco Scutari (2011).
Ph.D. School in Statistical Sciences, University of Padova.
Working Papers & Technical Reports
- Structure Variability in Bayesian Networks.
[ arXiv |
pdf ]
M. Scutari (2009).
Working Paper 13-2009, Department of Statistical Sciences, University of Padova.
Invited Speaks and Conference Presentations
- Genomic Selection with Linear Models and Rank Aggregation.
Genetics Institute, University College London (March 5, 2012). [ pdf ] - Graphical Models: Model Estimation and Validation.
Department of Statistical Sciences, University of Padova (September 27, 2011). [ pdf ] - On Identifying Significant Edges in Graphical Models.
Workshop on Probabilistic Problem Solving in Biomedicine, 13th Conference on Artificial Intelligence in Medicine (AIME'11), Bled (July 2, 2011). [ pdf ] - Measures of Variability for Graphical Models.
Genetics Institute, University College London (March 14, 2011). [ pdf ] - Bayesian Network Resampling for the Analysis of Functional Relationships.
Institut für Medizinische Informatik, Statistik und Epidemiologie (IMISE), Leipzig University (October 12, 2010). [ pdf ] - Constraint-based Bayesian Network Learning with Permutation Tests.
Statistics for Complex Problems: the Multivariate Permutation Approach and Related Topics, Archivio Antico, Palazzo del Bo, University of Padova (June 15, 2010). [ pdf ] - Structure Variability in Graphical Models.
Machine Learning / Intelligent Data Analysis Group, Institut für Softwaretechnik und Theoretische Informatik, Technische Universität Berlin (November 5, 2009). [ pdf ] - Comparing Bayesian Networks and Structure Learning Algorithms.
Institut für Medizinische Informatik, Statistik und Epidemiologie (IMISE), Leipzig University (October 20, 2009). [ pdf ] - Network Bayesiani: Selezione del Modello. (in Italian)
Department of Information Engineering, University of Padova (November 4, 2008). [ pdf ]
