Research

For a more complete list of publications, including all collaborative manuscripts, please refer to my Curriculum Vitae (CV).
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Selected Publications

Peer-Reviewed Original Research Articles (from a list of 59)


[29] Chiang, S., Guindani, M., Yeh, H-J., Dewar, S., Haneef, Z., Stern, J.M. and Vannucci, M. (2017) A Hierarchical Bayesian Model for the Identification of PET Markers Associated to the Prediction of Surgical Outcome After Anterior Temporal Lobe Resection Frontiers in Neuroscience In Press.

[28] Kook, J.H., Guindani, M., Zhang, L. and Vannucci, M. (2018) NPBayes-fMRI: Nonparametric Bayesian General Linear Models for Single- and Multi-Subject fMRI Data. Statistics in Biosciences In press. GUI Matlab available here .

[27] Warnick, R., Guindani, M., Erhardt, E., Allen, E., Calhoun, V. and Vannucci, M.(2017) A Bayesian Approach for Estimating Dynamic Functional Network Connectivity in fMRI Data. Journal of the American Statistical Association. In Press.

[26] Guindani, M., Johnson W.O. (2017) More nonparametric Bayesian inference in applications. Statistical Methods and Applications. In Press.

[25] Li, Q., Guindani, M., Reich, B.J., Bondell, H.D. and Vannucci, M. (2017). A Bayesian Mixture Model for Clustering and Selection of Feature Occurrence Rates under Mean Constraints. Statistical Analysis and Data Mining. Stat Anal Data Min: The ASA Data Sci Journal;10:393–409.

[24] Chiang, S., Guindani, M., Yeh, H.J., Haneef, Z., Stern, J.M. and Vannucci, M. (2017). A Bayesian Vector Autoregressive Model for Multi-Subject Effective Connectivity Inference using Multi-Modal Neuroimaging Data. Human Brain Mapping. Volume 38, Issue 3, Pages 1311–1332, DOI: 10.1002/hbm.23456.

[23] Wadsworth, W.D., Argiento, R., Guindani, M., Galloway-Pena, J., Shelbourne, S.A. and Vannucci, M. (2017). An Integrative Bayesian Dirichlet-Multinomial Regression Model for the Analysis of Taxonomic Abundances in Microbiome Data. BMC Bioinformatics. 18:94, DOI 10.1186/s12859-017-1516-0.

[22] Chekouo T, Stingo FC, Guindani M, Do K-A (2016) A Bayesian predictive model for imaging genetics with application to schizophrenia. Annals of Applied Statistics , 10 (3) , 1547-1571.

[21] Zhang, L., Guindani, M., Versace, F., Engelmann, J.M. and Vannucci, M. (2016). A Spatio-Temporal Nonparametric Bayesian Model of Multi-Subject fMRI Data. Annals of Applied Statistics, 10(2), 638-666. See also the supplementary material.

[20] Teo I, Fronczyk, K, Guindani M, Vannucci, M, Ulfers S, Hanasono M and Fingeret MC (2016). Salient Body Image and Psychosocial Concerns of Cancer Patients Undergoing Head and Neck Reconstruction. Head and Neck, 38(7), 1035-1042.

[19] Trevino V, Cassese A, Nagy Z, Zhuang X, Herbert J, Antzack P, Clarke K, Davies N, Rahman A, Campbell M, Guindani M, Bicknell R, Vannucci M. and Falciani F (2016). A Network Biology Approach Identifies Molecular Cross-talk between Normal Prostate Epithelial and Prostate Carcinoma Cells. PLoS Computational Biology, 12(4), e1004884. (PMCID: PMC4849722)

[18] Chiang S, Cassese A, Guindani M, Vannucci M, Yeh HJ, Haneef Z and Stern, JM (2016). Time-dependence of Graph Theory Metrics in Functional Connectivity Analysis. NeuroImage, 125, 601-615. (PMCID: PMC4895125)

[17] Fronczyk K, Guindani M, Hobbs BP, Ng C, Vannucci M (2015). A Bayesian nonparametric approach for functional data classification with application to hepatic tissue characterization. Cancer Informatics, 14(S5), 151-162.

[16] Waters AE, Fronczyk K, Guindani M, Baraniuk RG and Vannucci M (2015) A Bayesian Nonparametric Approach for the Analysis of Multiple Categorical Item Responses. Journal of Statistical Planning and Inference, 166, 52-66.

[15] Cassese A, Guindani M, Antczak P, Falciani F, Vannucci M (2015). A Bayesian Model for the Identification of Differentially Expressed Genes in Daphnia Magna Exposed to Munition Pollutants. Biometrics, 71, 803-811. Biometrics , 71 (1) , 188-97. See also the supplementary material. (PMID: 25771699, PMCID: PMC4880373)

[14] Graziani R, Guindani M, Thall PF (2015) Bayesian nonparametric estimation of targeted agent effects on biomarker change to predict clinical outcome Biometrics , 71 (1) , 188-97. See also the supplementary material. (PMCID: PMC4383707)

[13] Sun W, Reich B, Cai T, Guindani M, Schwartzman A (2015) False Discovery Control in Large-Scale Spatial Multiple Testing Journal of the Royal Statistical Society, Series B (Statistical Methodology), 77 (1) , 59-83. See also the supplementary material. (PMCID: PMC4310249)

[12] Zhang L, Guindani M, Vannucci M (2015). Bayesian models for functional magnetic resonance imaging data analysis. WIREs Computational Statistics, 7, 21-41.

[11] Cassese A, Guindani M, Vannucci, M (2014). A Bayesian Integrative Model for Genetical Genomics with Spatially Informed Variable Selection.Cancer Informatics, 13(S2) 29-37. See also the supplementary material. (PMCID:PMC4179607)

[10] Airoldi EM, Costa T, Bassetti F, Leisen F, Guindani M (2014) Generalized species sampling priors with latent Beta reinforcements. Journal of the American Statistical Association 109(508) , 1466-1480. See also the supplementary material. (PMCID: PMC4392726)

[9] Zhang L, Guindani M, Versace F, Vannucci M (2014) A Spatio-Temporal Nonparametric Bayesian Variable Selection Model of fMRI Data for Clustering Correlated Time Courses. Neuroimage 95 , 162-175. See also the supplementary material. (PMCID: PMC4076058)

[8] Guindani M, Sepulveda N, Paulino CD, Mueller P (2014) A Bayesian Semi-parametric Approach for the Differential Analysis of Sequence Counts Data. Journal of the Royal Statistical Society Series C (Applied Statistics) 63(3) , 385-404. See also the supplementary material. (PMCID: PMC4017673)

[7] Cassese A, Guindani M, Tadesse MG, Falciani F, Vannucci M (2014) A Hierarchical Bayesian Model for Inference on Copy Number Variants and their Associations to Gene Expression. The Annals of Applied Statistics 8(1) , 148-175. See also the supplementary material. (PMCID: PMC4018204)

[6] Stingo FC, Guindani M, Vannucci M, Calhoun VD (2013) An Integrative Bayesian Modeling Approach to Imaging Genetics. Journal of the American Statistical Association 108(503) , 876-891. (PMCID: PMC3843531)

[5] Reich BJ, Eidsvik J, Guindani M, Nail AJ, Schmidt AM (2011) A class of covariate-dependent spatiotemporal covariance functions for the analysis of daily ozone concentration. The Annals of Applied Statistics 5(4) , 2265-2687. (PMCID: PMC3998774)

[4] Guindani M, Mueller P, Zhang S (2009) A Bayesian discovery procedure Journal of the Royal Statistical Society Series B (Statistical Methodology) 71(5) , 905-25. (PMCID: PMC2914327)

[3] Petrone S, Guindani M, Gelfand AE (2009) Hybrid Dirichlet mixture models for functional data. Journal of the Royal Statistical Society Series B (Statistical Methodology) 71(4) , 755-82.

[2] Duan JA, Guindani M, Gelfand AE (2007) Generalized Spatial Dirichlet Process Models. Biometrika, 94(4) , 809-25.

[1] Guindani M and Gelfand AE (2006) Smoothness Properties and Gradient Analysis Under Spatial Dirichlet Process Models. Methodology and Computing in Applied Probability, 8(2) , 159-89.


Book Chapters

[6] Cassese A, Guindani M, Vannucci, M. (2016). iBATCGH: Integrative Bayesian Analysis of Transcriptomic and CGH data. In Statistical Analysis for High-Dimensional Data - The Abel Symposium 2014, Frigessi, A., Buhlmann, P., Glad, I., Langaas, M., Richardson, S. and Vannucci, M. (Eds). Springer Verlag, 105-123.

[5] Bassetti F., Leisen F., Airoldi E. and Guindani M. (2015) Species sampling priors for modeling dependence: an application to the detection of chromosomal aberrations. In Nonparametric Bayesian Inference in Biostatistics . Ed(s) Mitra R., Mueller P. Springer-Verlag, 2015.

[3] Tadesse M., Cassese A., Guindani M., Falciani F., Vannucci M. (2014) A Unified Method for CNV Detection and Association with Gene Expression. In Proceedings of the 47th Scientific Meeting of the Italian Statistical Society . CUEC Editrice: Cagliari, Italy.

[3] Guindani M., Zhang L., Versace F., Vannucci M. (2014) A Bayesian Variable Selection Model for the Clustering of Time Courses in FMRI data. In Proceedings of the 47th Scientific Meeting of the Italian Statistical Society . CUEC Editrice: Cagliari, Italy.

[2] Gelfand AE, Guindani M, Petrone S. (2007) Bayesian nonparametric modelling for spatial data using Dirichlet processes (with discussion). In Bayesian Statistics 8 . Oxford University Press.

[1] Guindani M, Do KA, Muller P, Morris J. (2006) Bayesian Mixture models for Gene Expression and Protein Profiles. In Bayesian Inference for Gene Expression and Proteomics . Ed(s) DO KA, Mueller P, Vannucci M. Cambridge University Press.