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Francesco C Stingo, PhD

Present Title & Affiliation

Primary Appointment

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

Research Interests

Dr. Stingo’s research focuses on the development of novel Bayesian methodologies motivated by real problems in the analysis of biomedical data with a specific interest in the integrative models, hierarchical Bayesian models and Bayesian models for variable selection. Dr. Stingo’s interests include also 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, Swartz MD, Vannucci M. A Bayesian Approach for the Identification of Genes and Gene-level SNP Aggregates in a Genetic Analysis of Cancer. Statistics and Its Interface. In Press.
2. Peterson C, Stingo FC and Vannucci M. Bayesian Inference of Multiple Gaussian Graphical Models. Journal of the American Statistical Association. In Press. NIHMSID: NIHMS568016.
3. Kry S, Molineu A, Kerns J, Faught A, Huang J, Pulliam K, Tonigan J, Alvarez P,Stingo FC, Followill DS. Institutional patient-specific intensity-modulated radiation therapy quality assurance does not predict unacceptable plan delivery as measured by IROC Houston’s head and neck phantom. International Journal of Radiation Oncology, Biology, Physics. In Press.
4. Ni Y, Stingo FC, Baladandayuthapani V. Integrative Bayesian Network Analysis of Genomic Data. Cancer Informatics. In Press.
5. Cowley AW, Moreno C, Jacob HJ, Peterson CB, Stingo FC, Ahn KW, Liu P, Vannucci M, Laud PW, Reddy P, Lazar J, Evans L, Yang C, Kurth T, Liang M. CHARACTERIZATION OF BIOLOGICAL PATHWAYS ASSOCIATED WITH A 1.37 MBP GENOMIC REGION PROTECTIVE OF HYPERTENSION IN DAHL S RATS. Physiol Genomics 46(11):398-410, 6/1/2014. e-Pub 4/8/2014. PMCID: PMC4042181.
6. Zhang L, Singh RR, Patel KP, Stingo F, Routbort M, You MJ, Miranda RN, Garcia-Manero G, Kantarjian HM, Medeiros LJ, Luthra R, Khoury JD. BRAF kinase domain mutations are present in a subset of chronic myelomonocytic leukemia with wild-type RAS. Am J Hematol 89(5):499-504, 5/2014. e-Pub 2/2014. PMCID: PMC24446311.
7. Wang SA, Hasserjian RP, Fox PS, Rogers HJ, Geyer JT, Chabot-Richards D, Weinzierl E, Hatem J, Jaso J, Kanagal-Shamanna R, Stingo FC, Patel KP, Mehrotra M, Bueso-Ramos C, Young KH, Dinardo CD, Verstovsek S, Tiu RV, Bagg A, Hsi ED, Arber DA, Foucar K, Luthra R, Orazi A. Atypical Chronic Myeloid Leukemia (aCML) BCR-ABL1-Negative is Clinicopathologically Distinct from Unclassifiable Myelodysplastic/Myeloproliferative Neoplasms (MDS/MPNU): a Bone Marrow Pathology Group Study. Blood 123(17):2645-51, 4/2014. e-Pub 3/2014. PMCID: PMCJournal In Process.
8. Doecke JD, Chekouo T, Stingo FC, and Do KA. miRNA target gene identification: sourcing miRNA-target gene relationships for the analyses of TCGA Illumina miSeq and RNA-Seq Hiseq platform data. International Journal of Human Genetics 14(1):17-22, 4/2014.
9. Ok CY, Hasserjian RP, Fox PS, Stingo F, Zuo Z, Young KH, Patel K, Medeiros LJ, Garcia-Manero G, Wang SA. Application of the International Prognostic Scoring System-Revised in therapy-related myelodysplastic syndromes and oligoblastic acute myeloid leukemia. Leukemia 28(1):185-9, 1/2014. e-Pub 6/21/2013. PMID: 23787392.
10. McKenzie EM, Balter PA, Stingo FC, Jones J, Followill DS, Kry SF. Reproducibility in patient-specific IMRT QA. J Appl Clin Med Phys 15(3):4741, 2014. e-Pub 5/2014. PMCID: PMC4048867.
11. Hunter LA, Krafft S, Stingo F, Choi H, Martel MK, Kry SF, Court LE. High Quality Machine-Robust Image Features: Identification in Non-Small Cell Lung Cancer Computed Tomography Images. Med Phys 40(12):121916-28, 12/2013. PMCID: PMC4108720.
12. Stingo FC, Guindani M, Vannucci M, Calhoun VD. An Integrative Bayesian Modeling Approach to Imaging Genetics. J Am Stat Assoc 108(105):876-891, 1/1/2013. PMCID: PMC3843531.
13. Yang C, Stingo FC, Ahn KW, Liu P, Vannucci M, Laud PW, Skelton M, O'Connor P, Kurth T, Ryan RP, Moreno C, Tsaih SW, 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. e-Pub 11/26/2012. PMCID: PMC3760736.
14. Stingo FC, Stanghellini E, Capobianco R. On the estimation of a binary response model in a selected population. J Stat Plan Inference 141(10):3293-3303, 10/1/2012. PMCID: PMC3968872.
15. Stingo FC, Vannucci M, Downey G. Bayesian Wavelet-based Curve Classification via Discriminant Analysis with Markov Random Tree Priors. Stat Sin 22(2):465-488, 4/1/2012. PMCID: PMC3993008.
16. Stingo FC, Chen YA, Tadesse MG, Vannucci M. Incorporating biological information into linear models: a Bayesian approach to the selection of pathways and genes. Ann Appl Stat 5(3):1978-2002, 9/1/2011. PMCID: PMC3650864.
17. 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.
18. Stingo FC, Chen YA, Vannucci M, Barrier M, Mirkes PE. A Bayesian Graphical Modeling Approach to MicroRNA Regulatory Network Inference. Ann Appl Stat 4(4):2024-2048, 2010. PMCID: PMC3740979.

Invited Articles

1. Peterson CB, Stingo FC. Discussion of "On the Prior and Posterior Distributions Used in Graphical Modelling" by M. Scutari. Bayesian Analysis 18(3):539-541, 9/2013.

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: 8/13/2014