Marzia Angela
Cremona

Publications

Articles

• Gansou, Y., Oualkacha, K., Cremona, M. A., & Lakhal-Chaieb, L. (2026). A functional approach to testing overall effect of interaction between DNA methylation and SNPs. Statistics in Medicine, 45(1-2), e70364. DOI : 10.1002/sim.70364
• Ashouri, M., Kin Hing Phoa, F., & Cremona, M. A. (2025). Analyzing Taiwanese traffic patterns on consecutive holidays through forecast reconciliation and prediction-based anomaly detection techniques. IEEE Access, 13, 108500-108518. DOI : 10.1109/ACCESS.2025.3581839
• Neumann, A., Zghal, Y., Cremona, M. A., Hajji, A., Morin, M., & Rekik, M. (2025). A data-driven personalized approach to predict blood glucose levels in type-1 diabetes patients exercising in free-living conditions. Computers in Biology and Medicine, 190, 110015. DOI : 10.1016/j.compbiomed.2025.110015
• Di Iorio, J., Cremona, M. A., & Chiaromonte, F. (2025). FunBIalign: a hierarchical algorithm for functional motif discovery based on mean squared residue scores. Statistics and Computing, 35(1), 11. DOI : 10.1007/s11222-024-10537-y
• Dang, H., Cremona, M. A., & Chiaromonte, F. (2025). smoothEM: A new approach for the simultaneous assessment of smooth patterns and spikes. Electronic Journal of Statistics, 19(2), 3835-3866. DOI : 10.1214/25-EJS2428
• Catania, G., Zanini, M., Cremona, M. A., Landa, P., Musio, M. E., Watson, R., Aleo, G., Aiken, L. H., Sasso, L., & Bagnasco, A. (2024). Nurses' intention to leave, nurse workload and in-hospital patient mortality in Italy: A descriptive and regression study. Health Policy, 143, 105032. DOI : 10.1016/j.healthpol.2024.105032
• Cremona, M. A., Doroshenko, L., & Severino, F. (2023). Functional motif discovery in stock market prices. SSRN Electronic Journal. DOI : 10.2139/ssrn.4642040
• Weissensteiner, M. H., Cremona, M. A., Guiblet, W. M., Stoler, N., Harris, R. S., Cechova, M., Eckert, K. A., Chiaromonte, F., Huang, Y.-F., & Makova, K. D. (2023). Accurate sequencing of DNA motifs able to form alternative (non-B) structures. Genome Research, 33, 907-922. DOI : 10.1101/gr.277490.122
• Jalili, V., Cremona, M. A., & Palluzzi, F. (2023). Rescuing biologically relevant consensus regions across replicated samples. BMC Bioinformatics, 24, 240. DOI : 10.1186/s12859-023-05340-x
• Cremona, M. A., & Chiaromonte, F. (2023). Probabilistic K-means with local alignment for clustering and motif discovery in functional data. Journal of Computational & Graphical Statistics, 32(3), 1119-1130. DOI : 10.1080/10618600.2022.2156522
• Severino, F., Cremona, M. A., & Dadié, É. (2022). COVID-19 effects on the Canadian term structure of interest rates. Review of Economic Analysis, 14(4), 471-502. DOI : 10.2139/ssrn.3762628
• Arbeithuber, B., Cremona, M. A., Hester, J., Barrett, A., Higgins, B., Anthony, K., Chiaromonte, F., Diaz, F. J., & Makova, K. D. (2022). Advanced age increases frequencies of de novo mitochondrial mutations in macaque oocytes and somatic tissues. Proceedings of the National Academy of Sciences (PNAS), 119(15), e2118740119. DOI : 10.1073/pnas.2118740119.2118740119
• Boschi, T., Di Iorio, J., Testa, L., Cremona, M. A., & Chiaromonte, F. (2021). Functional data analysis characterizes the shapes of the first COVID-19 epidemic wave in Italy. Scientific Reports, 11(1), 17054. DOI : 10.1038/s41598-021-95866-y
• Guiblet, W. M., Cremona, M. A., Harris, R. S., Chen, D., Eckert, K. A., Chiaromonte, F., Huang, Y.-F., & Makova, K. D. (2021). Non-B DNA: A major contributor to small- and large-scale variation in nucleotide substitution frequencies across the genome. Nucleic Acids Research, 49(3), 1497-1516. DOI : 10.1093/nar/gkaa1269
• Chen, D., Cremona, M. A., Qi, Z., Mitra, R. D., Chiaromonte, F., & Makova, K. D. (2020). Human L1 Transposition Dynamics Unraveled with Functional Data Analysis. Molecular Biology and Evolution, 37(12), 3576-3600. DOI : 10.1093/molbev/msaa194
• Arbeithuber, B., Hester, J., Cremona, M. A., Stoler, N., Zaidi, A., Higgins, B., Anthony, K., Chiaromonte, F., Diaz, F. J., & Makova, K. D. (2020). Age-related accumulation of de novo mitochondrial mutations in mammalian oocytes and somatic tissues. PLOS Biology, 18(7), e3000745. DOI : 10.1371/journal.pbio.3000745
• Di Iorio, J., Chiaromonte, F., & Cremona, M. A. (2020). On the bias of H-scores for comparing biclusters, and how to correct it. Bioinformatics, 36(9), 2955-2957. DOI : 10.1093/bioinformatics/btaa060
• Mei, H., Arbeithuber, B., Cremona, M. A., De Giorgio, M., & Nekrutenko, A. (2019). A high-resolution view of adaptive event dynamics in a plasmid. Genome Biology and Evolution, 11(10), 3022-3034. DOI : 10.1093/gbe/evz197
• Cremona, M. A., Xu, H., Makova, K. D., Reimherr, M., Chiaromonte, F., & Madrigal, P. (2019). Functional data analysis for computational biology. Bioinformatics, 35(17), 3211-3213. DOI : 10.1093/bioinformatics/btz045
• Guiblet, W. M. F., Cremona, M. A., Cechova, M., Harris, R., Kejnovska, I., Kejnovsky, E., Eckert, K., Chiaromonte, F., & Makova, K. D. (2018). Long-read sequencing technology indicates genome-wide effects of non-B DNA on polymerization speed and error rate. Genome Research, 28(12), 1767-1778. DOI : 10.1101/gr.241257.118
• Cremona, M. A., Pini, A., Cumbo, F., Makova, K. D., Chiaromonte, F., & Vantini, S. (2018). IWTomics : testing high-resolution sequence-based "Omics" data at multiple locations and scales. Bioinformatics, 34(13), 2289-2291. DOI : 10.1093/bioinformatics/bty090
• Cremona, M. A., Liu, B., Hu, Y., Bruni, S., & Lewis, R. (2016). Predicting railway wheel wear under uncertainty of wear coefficient, using universal kriging. Reliability Engineering & System Safety, 154, 49-59. DOI : 10.1016/j.ress.2016.05.012
• Campos-Sánchez, R., Cremona, M. A., Pini, A., Chiaromonte, F., & Makova, K. D. (2016). Integration and fixation preferences of human and mouse endogenous retroviruses uncovered with functional data analysis. PLOS Computational Biology, 12(6), e1004956. DOI : 10.1371/journal.pcbi.1004956
• Cremona, M. A., Sangalli, L. M., Vantini, S., Dellino, G. I., Pelicci, P. G., Secchi, P., & Riva, L. (2015). Peak shape clustering reveals biological insights. BMC Bioinformatics, 16, 349. DOI : 10.1186/s12859-015-0787-6

Chapitres d'un ouvrage collectif

• Di Iorio, J., Cremona, M. A., & Chiaromonte, F. (2025). Amplitude-invariant functional motif discovery. Dans Aneiros, G., Bongiorno, E.G., Goia, A., Hušková, M. (Ed). New Trends in Functional Statistics and Related Fields. IWFOS 2025. Contributions to Statistics (pp. 169-176). Springer. doi : 10.1007/978-3-031-92383-8_21.
• Cremona, M. A., Campos-Sánchez, R., Pini, A., Vantini, S., Makova, K. D., & Chiaromonte, F. (2017). Functional data analysis of “Omics” data: how does the genomic landscape influence integration and fixation of endogenous retroviruses?. Dans Aneiros, Bongiorno, Cao, Vieu (Ed). Functional Statistics and Related Fields (pp. 87-93). Springer. doi : 10.1007/978-3-319-55846-2.
• Azzimonti, L., Cremona, M. A., Ghiglietti, A., Ieva, F., Menafoglio, A., Pini, A., & Zanini, P. (2015). BarCamp : Technology foresight and statistics for the future. Dans Paganoni, Secchi (Ed). Advances in Complex Data Modeling and Computational Methods in Statistics (pp. 53-67). Springer. doi : 10.1007/978-3-319-11149-0_4.

Communications dans une conférence avec actes

• Neumann, A., Cremona, M. A., Hajji, A., Morin, M., & Rekik, M. (2025). Exploring the recent applications of artificial intelligence techniques for type-1 diabetes management. Operations Research and Artificial Intelligence in Healthcare Management.
• Neumann, A., Zghal, Y., Cremona, M. A., Morin, M., Hajji, A., Rekik, M., Moalla, E., & Mtiri, M. A. (2025). A comparative study of data-driven and personalized models trained to predict blood glucose levels of type-1 diabetes patients exercising in free-living conditions. CIRRELT Optimization Days 2025, Montréal, Canada.
• Arbeithuber, B., Hester, J., Cremona, M. A., Barret, A., Higgins, B., Anthony, K., Diaz, F. J., & Makova, K. D. (2021). Advanced age increases frequencies of de novo mitochondrial mutations in macaque oocytes and somatic tissues. Abstracts from the Environmental Mutagenesis and Genomics Society 52nd Annual Meeting.
• Eckert, K. A., Hile, S. E., Guiblet, W. M. F., Cremona, M. A., Stein, M. E., Huang, Y. F., Chiaromonte, F., & Makova, K. (2020). G-quadruplex sequences are barriers to replicative DNA polymerases and hotspots of mutagenesis. Abstracts from the Environmental Mutagenesis and Genomics Society 51st Annual Meeting, Environmental and Molecular Mutagenesis.
• Torres-Gonzalez, E., Arbeithuber, B., Hester, J., Cremona, M. A., Stoler, N., Higgins, B., Anthony, K., Chiaromonte, F., Diaz, F. J., & Makova, K. (2020). Duplex sequencing uncovers age-related increase in the frequency of de novo indels in mouse mitochondrial DNA. Abstracts from the 53rd European Society of Human Genetics (ESHG) Conference: e-Posters. European Journal of Human Genetics.
• Cremona, M. A., Campos-Sánchez, R., Pini, A., Vantini, S., Makova, K. D., & Chiaromonte, F. (2016). Functional data analysis at the boundary of "Omics". Proceedings of IWSM 2016, 31st International Workshop on Statistical Modelling.
• Cremona, M. A., Pellici, P. G., Riva, L., Sangalli, L., Secchi, P., & Vantini, S. (2014). Cluster analysis on shape indices for ChIP-seq data. Proceedings of SIS 2014, 47th Scientific Meeting of the Italian Statistical Society.
• Cremona, M. A., Riva, L., Sangalli, L., Secchi, P., & Vantini, S. (2013). Clustering ChIP-seq data using peak shape. Proceedings of SCo 2013, 8th Conference on Complex Data Modeling and Computationally Intensive Statistical Methods for Estimation and Prediction.

Communications dans une conférence sans actes

• Cremona, M. A. (2025). funBlalign: a hierarchical algorithm for functional motif discovery. HiTEc & CoDES 2025, Etats-Unis d'Amérique.
• Cremona, M. A. (2025). Selection of functional predictors and smooth coefficient estimation for scalar-on-function regression models. CMS Summer Meeting 2025, Québec, Canada.
• Cremona, M. A. (2025). Amplitude-invariant functional motif discovery. IWFOS 2025 International Workshop on Functional and Operational Statistics, Novara, Italie.
• Neumann, A., Zghal, Y., Cremona, M. A., Hajji, A., Morin, M., & Rekik, M. (2025). A data-driven personalized approach to predict blood glucose levels in type-1 diabetes patients exercising in free-living conditions. Journée de l optimisation / Optimization Days, Montréal, Canada.
• Cremona, M. A. (2025). Local clustering and motif discovery of functional data. Statistics and Data Science Seminar at Aubum University, Etats-Unis d'Amérique.
• Cremona, M. A. (2025). Local clustering and motif discovery of functional data. Quantitative Theory and Methods Seminar at Emory University, Atlanta, Etats-Unis d'Amérique.
• Cremona, M. A. (2025). Local clustering and motif discovery of functional data. Séminaire au Département d'informatique et de génie logiciel de l'Université Laval, Québec, Canada.
• Cremona, M. A., Doroshenko, L., & Severino, F. (2024). Functional motif discovery in stock market prices. 17th Annual Meeting of the Academy of Behavioral Finance & Economics (ABF&E), Los Angeles, Etats-Unis d'Amérique.
• Cremona, M. A., Doroshenko, L., & Severino, F. (2024). Functional motif discovery in stock market prices. 26th International Conference on Computational Statistics (COMPSTAT), Justus-Liebig-University Giessen, Allemagne.
• Landa, P., Cremona, M. A., Murazzano, L., Gartner, J.-B., & Côté, A. (2024). A predictive model for patient length of stay and hospital readmission for specialized respiratory diseases hospital. 50th annual meeting of the euro working group on Operational Research Applied to Health Services (ORAHS), Turin, Italie.
• Cremona, M. A. (2024). Functional motif discovery in stock market prices. EcoSta 2024, 7th International Conference on Econometrics and Statistics, Beijing, Chine (RPC).
• Cremona, M. A. (2023). Functional motif discovery in stock market prices. ERCIM 2023, joint conference CFE-CMStatistics, Berlin, Allemagne.
• Cremona, M. A. (2023). SmoothEM: a new approach for the simultaneous assessment of smooth curves and spikes. Departmental Seminar, Catholic University of the Sacred Hear, Fairfield, Etats-Unis d'Amérique.
• Cremona, M. A. (2023). SmoothEM: a new approach for the simultaneous assessment of smooth curves and spikes. DSS Statistics Seminar, Sapienza University of Rome, En ligne, Italie.
• Cremona, M. A. (2023). Statistical learning methods for functional data: applications in “omics" and biomedical sciences. Conférence du centre de recherche de CHU Québec – Université Laval, Québec, Canada.
• Doroshenko, L., Cremona, M. A., & Severino, F. (2022). Functional motif discovery in stock market prices. Stochastic Modeling and Computational Statistics talk; Pennsylvania State University, Eberly College of Science, Department of Statistics, University Park, Etats-Unis d'Amérique.
• Cremona, M. A. (2022). Machine learning methods for functional data in “Omics” research. ISSNAF Young Investigator Gerla Award Symposium, En ligne, Etats-Unis d'Amérique.
• Cremona, M. A. (2022). Functional data analysis of high resolution “Omics” data. Genomic Seminar, Pennsylvania State University, State College, Etats-Unis d'Amérique.
• Cremona, M. A. (2022). Probabilistic clustering with local alignment of Italian COVID-19 death curves. ECDA 2022 European Conference on Data Analysis, En ligne, Italie.
• Cremona, M. A. (2022). smoothEM: a new approach for the simultaneous assessment of smooth curves and spikes. COMPSTAT 2022, 24th International Conference on Computational Statistics.
• Cremona, M. A. (2022). Local clustering and motif discovery of functional data: applications in ''omics'', biomedical sciences and finance. Workshop EMbeDS, En ligne.
• Cremona, M. A. (2022). COVID-19 in Italy: characterizing the shapes of epidemic waves through Functional Data Analysis. SIS2022, 51st Scientific Meeting of the Italian Statistical Society.
• Cremona, M. A. (2022). COVID-19 effects on the Canadian term structure of interest rates. ISBIS Conference on ''Statistics and Data Science in Business and Industry''.
• Cremona, M. A. (2022). smoothEM: a new approach for the simultaneous assessment of smooth curves and spikes. SSC 2022 Statistical Society of Canada Annual Meeting, En ligne.
• Cremona, M. A., Severino, F., & Dadié, É. (2021). COVID-19 effects on the Canadian term structure of interest rates. ERCIM 2021, joint conference CFE-CMStatistics, London (Virtuel), Royaume-Uni.
• Severino, F., Cremona, M. A., & Dadié, É. (2021). COVID-19 effects on the Canadian term structure of interest rates. XLV AMASES Conference, Università Mediterranea di Reggio Calabria, Reggio Calabria (Virtuel), Italie.
• Cremona, M. A., Chiaromonte, F., & Makova, K. D. (2021). Functional data analysis of high-resolution ''Omics'' data. ISI WSC 2021, World Statistics Congress, En ligne.
• Cremona, M. A., Boschi, T., Di Iorio, J., Testa, F., & Chiaromonte, F. (2021). Functional data analysis characterizes the shapes of the COVID-19 epidemics in Italy. Statistics 2021 Canada, Virtuel, Canada.
• Cremona, M. A., Boschi, T., Di Iorio, J., Testa, L., & Chiaromonte, F. (2021). Functional data analysis characterizes the shapes of the COVID-19 epidemics in Italy. SSC 2021 Statistical Society of Canada Annual Meeting, Virtuel, Canada.
• Cremona, M. A., Boschi, T., & Chiaromonte, F. (2021). Probabilistic local clustering of misaligned functional data : analysis of Italian COVID-19 death curves. IWFOS 2021 International Workshop on Functional and Operatorial Statistics, Virtuel.
• Cremona, M. A., Chiaromonte, F., & Makova, K. D. (2020). Functional data analysis applications to Omics sciences. Women in Data Science, Saguenay, Canada.
• Cremona, M. A., Chiaromonte, F., & Makova, K. D. (2019). Functional data analysis applications to Omics sciences. ERCIM 2019, joint conference CFE-CMStatistics, London, Royaume-Uni.
• Cremona, M. A., & Chiaromonte, F. (2019). Probabilistic K-mean with local alignment for functional motif discovery. ENAR 2019 Spring Meeting, Philadelphia, Etats-Unis d'Amérique.
• Cremona, M. A., Chiaromonte, F., & Makova, K. D. (2018). Using Interval-Wise Testing to investigate high-resolution "Omics" data at multiple locations and scales. ERCIM 2018, joint conference CFE-CMStatistics, Pisa, Italie.
• Cremona, M. A., & Chiaromonte, F. (2018). Probabilistic K-mean with local alignment to locally cluster curves and discover functional motifs. Worshop on Advances in Functional Data Analysis : cluster, location and shape, Rennes, France.
• Cremona, M. A. (2018). Probabilistic K-mean with local alignment for functional motif discovery. ISSNAF Annual Event (ISSNAP young investigators award finalists' presentations), Washington, Etats-Unis d'Amérique.
• Cremona, M. A., & Chiaromonte, F. (2018). Probabilistic K-mean with local alignment for functional motif discovery. JSM 2018, Joint Statistical Meetings, Vancouver, Canada.
• Cremona, M. A. (2018). Functional data analysis applications in "Omics" sciences. NRC 2018, 20th Meeting of New Researchers in Statistics and Probability, Burnaby, Canada.
• Cremona, M. A., & Chiaromonte, F. (2018). Probabilistic K-mean with local alignment for functional motif discovery. DSSV 2018, Data Science, Statistics & Visualization, Wien, Autriche.
• Cremona, M. A. (2018). Discovering functional motifs in "Omics" curves using probabilistic K-mean with local alignment. Workshop on Emerging Methods for Sequence Analysis, Pennsylvania State University, Pennsylvania, Etats-Unis d'Amérique.
• Cremona, M. A., & Chiaromonte, F. (2017). Probabilistic K-mean with local alignment for functional motif discovery. ERCIM 2017, joint conference CFE-CMStatistics, London, Royaume-Uni.
• Cremona, M. A. (2017). Functional Data Analysis testing and linear modeling for high-resolution "Omics" data. 2017 UCLA CGSI Computational Genomics Summer Institute, Los Angeles, Etats-Unis d'Amérique.
• Cremona, M. A., Campos-Sánchez, R., Pini, A., Vantini, S., Makova, K. D., & Chiaromonte, F. (2017). Functional data analysis of "Omics" data: how does the genomic landscape influence integration and fixation of endogenous retroviruses?. IWFOS 2017, 4th International Workshop on Functional and Operatorial Statistics, La Coruña, Espagne.
• Cremona, M. A. (2016). Functional Data Analysis for "Omics" (lightning talk). 9th Annual Postdoctoral Research Exhibition, Pennsylvania State University, Pennsylvania, Etats-Unis d'Amérique.
• Cremona, M. A., Pelicci, P. G., Riva, L., Sangalli, L., Secchi, P., & Vantini, S. (2014). ChIP-seq peak shape clustering analysis. EPIGEN-MiChroNetwork Chromatin Seminar "Gene Regulation through Chromatin Structure", Milano, Italie.
• Cremona, M. A., & Parodi, A. (2014). Peak shape cluster analysis reveals novel biological insights. Workshop on Statistics for Omics, Politecnico di Milano, Milan, Italie.
• Cremona, M. A., Pelicci, P. G., Riva, L., Sangalli, L., Secchi, P., & Vantini, S. (2014). Cluster analysis on shape indices for ChIP-seq data. SIS 2014, 47th Scientific Meeting of the Italian Statistical Society, Cagliari, Italie.
• Cremona, M. A. (2014). Peak shape cluster analysis reveals novel biological insights. IEO-IIT-PoliMi Joint Meeting on Genomic Computing, Politecnico di Milano, Milan, Italie.
• Cremona, M. A., Sangalli, L., Secchi, P., & Vantini, S. (2013). Clustering of ChIP-seq data through peak shape. ABS 2013 Applied Bayesian Statistics School "Bayesian Methods for Variable Selection with Applications to High Dimensional Data", Como, Italie.

Présentations dans un séminaire de recherche

• Cremona, M. A., Boschi, T., Di Iorio, J., Testa, L., & Chiaromonte, F. (2021). Statistical learning methods for functional data with application to the study of COVID-19 in Italy. CIRRELT Webinar, En ligne, Canada.
• Cremona, M. A., & Chiaromonte, F. (2020). Probabilistic K-mean with local alignment to locally cluster curves and discover functional motifs. Séminaires du Département de mathématiques et de statistique (Université Laval), Québec, Canada.
• Cremona, M. A., Boschi, T., Di Iorio, J., Testa, L., & Chiaromonte, F. (2020). The shapes of an epidemic: Using functional data analysis to characterize COVID-19 in Italy. R. Clifton Bailey seminar statistics seminars (George Mason University), En ligne.
• Cremona, M. A., Boschi, T., Di Iorio, J., Testa, L., & Chiaromonte, F. (2020). The shapes of an epidemic: Using functional data analysis to characterize COVID-19 in Italy. Séminaires de statistiques du Département de mathématiques (Université du Québec à Montréal), En ligne, Canada.
• Cremona, M. A., & Chiaromonte, F. (2019). Probabilistic K-mean with local alignment to locally cluster curves and discover functional motifs. University of Augsburg, Augsburg, Allemagne.
• Cremona, M. A. (2019). Using functional data analysis to exploit high-resolution "Omics" data. Clemson University, Clemson, Etats-Unis d'Amérique.
• Cremona, M. A. (2019). Using functional data analysis to exploit high-resolution "Omics" data. American University, Washington, Etats-Unis d'Amérique.
• Cremona, M. A. (2019). Using functional data analysis to exploit high-resolution "Omics" data. University of Canterbury, Christchurch, Nouvelle Zélande.
• Cremona, M. A. (2019). Using functional data analysis to exploit high-resolution "Omics" data. Statistics Department Colloquium, Pennsylvania State University, University Park, Etats-Unis d'Amérique.
• Cremona, M. A. (2019). Using functional data analysis to exploit high-resolution "Omics" data. University of Otago, Dunedin, Nouvelle Zélande.
• Cremona, M. A. (2019). Using functional data analysis to exploit high-resolution "Omics" data. Wayne State University, Detroit, Etats-Unis d'Amérique.
• Cremona, M. A. (2019). Using functional data analysis to exploit high-resolution "Omics" data. University of Glasgow, Glasgow, Royaume-Uni.
• Cremona, M. A. (2019). Using functional data analysis to exploit high-resolution "Omics" data. University of South Florida, Tampa, Etats-Unis d'Amérique.
• Cremona, M. A. (2018). Using functional data analysis to exploit high-resolution "Omics" data. Miami University, Oxford, Etats-Unis d'Amérique.
• Guiblet, W. M. F., Cremona, M. A., Cechova, M., & Harris, R. (2017). Non-B DNA affects polymerase progression and error rates in sequencers and living cells. Genomics Seminar, Pennsylvania State University, University Park, Etats-Unis d'Amérique.
• Cremona, M. A. (2017). Exploiting high-resolution "Omics" data with Functional Data Analysis. Statistics Department Seminar, Pennsylvania State University, University Park, Etats-Unis d'Amérique.
• Cremona, M. A., & Chiaromonte, F. (2017). Discovering motifs in "Omics" signals using local clustering of curves. Sant'Anna School of Advanced Studies, Pisa, Italie.
• Cremona, M. A. (2017). Functional Motif Discovery for "Omics" curves. Genomics Seminar, Pennsylvania State University, University Park, Etats-Unis d'Amérique.
• Cremona, M. A. (2016). Discovering motifs in "Omics" signals using local clustering of curves. Stochastic Modeling and Computational Statistics Seminar, Pennsylvania State University, University Park, Etats-Unis d'Amérique.
• Cremona, M. A. (2016). Peak shape clustering: an application to GATA-1. Medical Genomics Seminar, Pennsylvania State University, University Park, Etats-Unis d'Amérique.
• Cremona, M. A. (2016). A functional data analysis approach to "Omics" data. Genomics Seminar, Pennsylvania State University, University Park, Etats-Unis d'Amérique.

Rapports de recherche

• Bergeron, S., Vigreux, L., Brès, L., Barbeau-Baril, J., Garrido, S. R., & Cremona, M. A. (2020). Baromètre 2020 de l'achat responsable.

Affiches

• Campos-Sánchez, R., Cremona, M. A., Pini, A., Chiaromonte, F., & Makova, K. D. (2016). « Integration and fixation preferences of human and mouse endogenous reroviruses uncovered with functional data analysis », The Biology of Genomes. [Affiche].
• Campos-Sánchez, R., Cremona, M. A., Pini, A., Chiaromonte, F., & Makova, K. D. (2016). « Integration and fixation preferences of human and mouse endogenous retroviruses uncovered with functional data analysis », Center for Medical Genomics Retreat, Pennsylvania State University. [Affiche].
• Cremona, M. A., Riva, L., Sangalli, L., Secchi, P., & Vantini, S. (2013). « Clustering ChIP-seq data using peak shape », SCo 2013, 8th Conference on Complex Data Modeling and Computationally Intensive Statistical Methods for Estimation and Prediction. [Affiche].

Autres

• Brès, L., Cremona, M. A., Dumas, M., Outman, O., & Saulnier, A.-M. (2022). Sustainable procurement in private sector organizations. In Stritch J. M., Darnall N., Chen Y., Fox A., Swanson J., Adell A., Molino J., Wierzbicki A., Brès L., Cremona M. A., Dumas M., Outmani O., Saulnier A.-M., von Schuckmann L., Caranta R., Hannerz J., Vykhrystyuk K., Loueyraud S. (Eds.) 2022 Global review of sustainable public procurement. Paris: United-Nation environment Programme (UNEP).
• Cremona, M. A. (2019). Software : IWTomics - Interval-wise Testing for Omics Data, Bioconductor R package and Galaxy tool.
• Cremona, M. A. (2015). Software : SIC-ChIP - Shape Index Clustering for ChIP-seq peaks. Command line R script.

Activités de recherche en cours

Titre de l'activité	Chercheur(s)	Organisme subventionnaire	Programme	Dates
Soutien de la FSA - Chaire de recherche en apprentissage statistique	Principal Marzia Angela Cremona	Université Laval - Fonds internes		2025-09-01 au 2030-08-31
Chaire de recherche FRQ-IVADO en apprentissage statistique	Principal Vincent Poitout Autres chercheurs	Fonds de recherche du Québec - Nature et technologies	Chaire en partenariat FRQ-IVADO	2025-09-01 au 2030-08-31
FunBIalign: A hierarchcal algorithm for functional motif discovery based on mean squared residue scores	Principal Marzia Angela Cremona	Université Laval - Fonds internes	Soutien à la recherche (SAR) FSA - Volet 13 : Valorisation de la publication dans des revues classées A et B	2025-08-06 au 2026-04-30
Analyzing Taiwanese traffic patterns on consecutive holidays through forecast reconciliation and prediction-based anomaly detection techniques	Principal Marzia Angela Cremona	Université Laval - Fonds internes	Soutien à la recherche (SAR) FSA - Volet 3: Aide à la publication	2025-06-07 au 2026-04-30
ACIAP-DT1 : un Agent Conversationnel Intelligent pour un Accompagnement Personnalisé dans la gestion du Diabète de Type 1	Principal Monia Rekik Autres chercheurs	Université Laval - Fonds internes		2025-06-06 au 2026-04-30
Quantifying the Relationship between Increasing Maritime Traffic and Atmospheric Pollution in the Artic	Principal Marzia Angela Cremona	Université Laval - Fonds internes	Soutien à la recherche (SAR) FSA - Volet 15 : Subvention facultaire d'amorçage de projets de recherche	2024-12-02 au 2026-04-30
Création d’une macro automatisée permettant d’estimer les coûts engendrés par des patients au sein des bases de données médico-administratives du Québec.	Principal Jason Robert Guertin Autres chercheurs	Fonds de recherche du Québec - Santé		2023-10-01 au 2026-09-30
Exploitation de méthodes statistiques pour les données fonctionnelles dans les études "omiques", longitudinales et épidémiologiques	Principal Marzia Angela Cremona	Fonds de recherche du Québec - Santé	Chercheur-boursier Juniors 1 et 2, Seniors	2023-07-01 au 2027-11-30
Économies salariales de la professeure Marzia Angela Cremona	Principal Marzia Angela Cremona	Université Laval - Fonds internes		2023-07-01 au 2027-11-30
Exploitation de méthodes statistiques pour les données fonctionnelles dans les études "omiques"	Principal Marzia Angela Cremona	Fonds de recherche du Québec - Santé	Établissement de jeunes chercheurs - Juniors 1	2023-07-01 au 2027-06-30

Affiliations de recherche en cours

• Professeure adjointe associée, Department of Statistics of the Pennsylvania State University (2019 - ...)
• Chercheuse universitaire, Centre de recherche du CHU de Québec-Université Laval, Axe Santé des populations et pratiques optimales en santé (2019 - ...)
• Chercheuse membre, Institut Intelligence et Données de l'Université Laval (IID_UL) (2020 - ...)
• Membre, Centre interuniversitaire de recherche sur les réseaux d'entreprise, la logistique et le transport (CIRRELT) (2019 - 2027)
• Membre régulier, Center for Medical Genomics (2019 - ...)
• Membre collaborateur, Centre de Recherche en Données Massives de l'Université Laval (CRDM-UL) (2020 - ...)
• Membre régulier, StatLab, Centre de Recherches Mathématiques (CRM) (2022 - ...)
• Membre, Laboratoire Interdisciplinaire de la Responsabilité Sociale des Entreprises (LIRSE) (2022 - ...)
• Titulaire, Chaire de recherche en apprentissage statistique (2025 - ...)

Encadrement étudiant

Maîtrise avec mémoire

• Directrice de recherche
  • Antoine Bouchard (Automne 2025 - ...)
  • Hesam Hafezalseheh (Été 2023 - Été 2024)
• Codirectrice de recherche
  • Mohamed Aziz Mtiri (Hiver 2025 - ...)
  • Yessine Zghal (Hiver 2024 - Hiver 2026)
  • Pathe Conte (Été 2021 - Automne 2021)
  • Pathe Conte (Hiver 2020 - Été 2020)

Doctorat

• Directrice de recherche
  • El Hadji Tamsir Babou Dieng (Hiver 2025 - ...)
  • Hedayat Fathi (Automne 2021 - ...)
  • Matteo Fuligni (Hiver 2026 - ...)
  • Nina Frischherz (Automne 2025 - ...)
• Codirectrice de recherche
  • Yvelin Gansou (Hiver 2024 - ...)

Contribution à l'avancement de la discipline

Organisation de conférence(s)

• Organisatrice et présidente d'une séance, ERCIM 2023, joint conference CFE-CMStatistics (2023)
• Organisateur et président d'une séance en ligne, ERCIM 2021, joint conference CFE-CMStatistics (2021)
• Organisatrice et responsable de session, ERCIM 2019, joint conference CFE-CMStatistics (2019)
• Session organizer, ERCIM 2019, joint conference CFE-CM Statistics (2019)
• Session organizer and chair, ERCIM 2018, joint conference CFE-CMStatistics (2018)
• Journal club organizer, 2017 UCLA CGSI Computational Genomics Summer Institute (2017)
• Session co-organizer, StaTalk on Biostistics (2015)
• Conference co-organizer, SCo-BarCamp "Technology Foresight and Statistics for the Future" (2013 - 2016)

Responsabilités éditoriales

• Frontiers in Genetics (revue scientifique, éditeur de révision) (2022 - 2025)

Direction scientifique / Responsable scientifique

• Membre du comité du programme scientifique, ERCIM 2023, joint conference CFE-CMStatistics (2023)
• Membre du comité du programme scientifique. ERCIM 2020, joint conference CFE-CMStatistics, Virtual conference (2020)

Participation à des jurys d'organismes de subvention

• Fonds de recherche du Québec - Santé (FRQS) (2024 - 2025)
• Fonds de recherche du Québec - Nature et techonologies (FRQNT) (2024 - 2025)
• Univresité La Sapienza (2023 - 2024)
• CRSNG Subvention Alliance (2021 - 2022)

Implications universitaires et facultaires

Faculté

• Membre du Comité facultaire de la bibliothèque (2022 - 2026)

Prix et distinctions

Prix et distinctions

• Distinction Socrate (2023 - 2024)
• Médaille de la recherche
  • (2023 - 2024)
  • (2022 - 2023)
  • (2021)
  • (2020)
  • (2020 - 2021)
• Finalist for ISSNAF (Italian Scientists and Scholars of North America) young investigators award (2018)
• Travel support to attend NRC 2018, 20th Meeting of New Researchers in Statistics and Probability (2018)
• Best presentation of an Early Career Investigator at the joint conference CFE-CMStatistics (2017)
• Postdoctoral travel award, The Pennsylvania State University (2017)
• Travel support to attend 2017 UCLA CGSI Computational Genomics Summer Institute, Long course (2017)
• International mobility award, Politecnico di Milano (2014)
• Ph. D. scholarship in the field of "Genomic Computing" (2012 - 2015)