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Francesco C Stingo, PhD

Present Title & Affiliation

Primary Appointment

Assistant Professor, Department of Biostatistics, Division of Quantitative Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX

Research Interests

My research focuses on the development of novel Bayesian methodologies motivated by real problems in the analysis of DNA microarray data with a particular interest in models that integrate different sources of biological information. I am also interested in Graphical models, Bayesian variable selection and in wavelet-based methods for the analysis of functional data.

Office Address

The University of Texas MD Anderson Cancer Center
1400 Pressler Dr.
Houston, TX 77230
Room Number: Pickens Academic Tower, FCT 4.6042
Email: FStingo@mdanderson.org

Education & Training

Degree-Granting Education

2010 University of Florence, Florence, Italy, PHD, Statistics

Postgraduate Training

1/2010-7/2011 Postdoctoral Fellow, Rice University, Houston, TX

Honors and Awards

2011 Best PhD thesis 2010, Italian Statistical Society
2007-2009 Ph.D. Scholarship, University of Florence

Selected Publications

Peer-Reviewed Original Research Articles
1. Stingo, FC, Guindani M, Vannucci M, Calhoun VD. An Integrative Bayesian Modeling Approach to Imaging Genetics. Journal of the American Statistical Association. In Press.
2. Yang C, Stingo FC, Ahn KW, Liu P, Vannucci M, Laud PW, Skelton M, O'Connor P, Kurth T, Moreno, C., Tsaih, S., Patone G, Hummel O, Jacob HJ, Liang M, Cowley AW. Increased Proliferative Cells in the Medullary Thick Ascending Limb of the Loop of Henle in the Dahl Salt-Sensitive Rat. Hypertension 61(1):208-215, 1/2013.
3. Stingo FC, Vannucci M, Downey G. Bayesian Wavelet-based Curve Classification via Discriminant Analysis with Markov Random Tree Priors. Statistica Sinica 22(2):465-488, 2012.
4. Stingo FC, Vannucci M. Variable Selection for Discriminant Analysis with Markov Random Field Priors for the Analysis of Microarray Data. Bioinformatics 27(4):495-501, 2/15/2011. e-Pub 12/14/2010. PMCID: PMC3105481.
5. Stingo FC, Chen YA, Tadesse MG, Vannucci M. Incorporating biological information into linear models: a Bayesian approach to the selection of pathways and genes. Annals of Applied Statistics 5(3):1978-2002, 2011.
6. Stingo FC, Stanghellini E, Capobianco R. On the estimation of a binary response model in a selected population. Journal of Statistical Planning and Inference 141:3293-3303, 2011.
7. Stingo FC, Chen YA, Vannucci M, Barrier M, Mirkes PE. A Bayesian Graphical Modeling Approach to MicroRNA Regulatory Network Inference. Annals of Applied Statistics 4(4):2024-2048, 2010.

Book Chapters
1. Stingo FC, Vannucci M. Bayesian Models for Integrative Genomics. In: Advances in Statistical Bioinformatics: Models and Integrative Inference for High-Throughput Data. Ed(s) K-A Do, ZS Qin, M Vannucci. Cambridge University Press, 2013.
2. Vannucci M, Stingo FC. Bayesian Models for Variable Selection that Incorporate Biological Information (with discussion). In: Bayesian Statistics 9. Oxford University Press, 2011.

Last updated: 4/24/2013