In journals
Montin, A., Brazzale, A. R., Menardi, G., and Sottosanti, A. (2023) Locating \(\gamma\)-ray sources on the celestial sphere via modal clustering. Statistical Methods & Applications. (link)
Ianniello, A., Sottosanti, A., Borriello, G., and Vincenti, M. (2023) Perception of Quality of Life and Fatigue in Multiple Sclerosis Patients Treated with High-Dose Vitamin D. Clinical and Translational Neuroscience 7(2):12-27. (link)
Righelli, D., Sottosanti, A., and Risso, D. (2023) Designing spatial transcriptomic experiments. Nature Methods 20(3):355-356. (link)
Sottosanti, A., and Risso, D. (2023) Co-clustering of Spatially Resolved Transcriptomic Data. The Annals of Applied Statistics 17(2):1444-1468. (link)
Sottosanti, A., Risso, D., and Castiglione, C. (2022) Contributed discussion: “Bayesian Nonstationary and Nonparametric Covariance Estimation for Large Spatial Data” by B. Kidd and M. Katzfuss. Bayesian Analysis 17(1):337-339. (link)
Hayden, E., Airoldi, C., Scotti, L., Bellan, M., Sottosanti, A., Bergamasco, P., Salamina, L., Capponi, A., Sainaghi, P.P., and Pirisi, M. (2021) Modelling hospital bed necessity for COVID-19 patients during the decline phase of the epidemic trajectory. Minerva Respiratory Medicine 60(2):29-35. (link)
Costantin, D., Sottosanti, A., Brazzale, A. R., Bastieri, D., Fan, J. (2022) Bayesian Mixture Modeling of the High-Energy Photon Counts collected by the Fermi Large Area Telescope. Statistical Modelling 22(3):175-198. (link)
In volumes
Sottosanti, A., Costantin, D., Bastieri, D., and Brazzale, A. R. (2019). Discovering and Locating High-Energy Extra-Galactic Sources by Bayesian Mixture Modelling. New Statistical Developments in Data Science (A. Petrucci, F. Racioppi and R. Verde Eds.), Springer Proceedings in Mathematics & Statistics, 288, 135-148. (link)
Caponera, A., Denti, F., Rigon, T., Sottosanti, A., and Gelfand, A. (2018). Hierarchical Spatio- Temporal Modeling of Resting State fMRI Data. Studies in Neural Data Science (A. Canale, D. Durante, L. Paci and B. Scarpa Eds.), Springer Proceedings in Mathematics & Statistics, 257, 111-130. (link)
In proceedings
Sottosanti, A. and Risso, D. (2021) Co-clustering Models for Spatial Transciptomics: Analysis of a Human Brain Tissue Sample. Proceedings of the 50th Scientific meeting of the Italian Statistical Society.
Sottosanti, A., Bernardi, M., Campos, L., Siemiginowska, A. and van Dyk, D.A. (2019) Continuous time hidden Markov models for astronomical gamma-ray light curves. Proceedings of the 34th International Workshop on Statistical Modelling (IWSM 2019), 7-12 July 2019, Guimarães (Portugal). Best student paper
Busatto, C., Sottosanti, A. and Bernardi, M. (2019). Bayesian Variable Selection for High Dimensional Logistic Regression. Smart Statistics for Smart Applications: Book of Short Papers SIS2019, 18-21 June 2019, Milan (Italy).
Sottosanti, A., Bernardi, M., Brazzale, A.R. (2018) Mining signals of astronomical sources via Bayesian nonparametric mixture modelling. Proceedings of the 33rd International Workshop on Statistical Modelling (IWSM 2018), 16-20 July, Bristol (UK). Runner-up as best student paper
Sottosanti, A., Bastieri, D., Brazzale, A.R. (2017). Bayesian Mixture Models for the Detection of High-Energy Astronomical Sources. Statistics and Data Science: new challenges, new genera- tions, 28-30 June 2017, Florence (Italy).
Under review