Pubblications
2024
Chordal-NMF with Riemannian Multiplicative Update. Esposito F., Andersen Ang (2024) ArXiv Preprint. doi: 10.48550/arXiv.2405.12823.
Review of Patient Gene Profiles Obtained through a Non-Negative Matrix Factorization-Based Framework to Determine the Role Inflammation Plays in Neuroblastoma Pathogenesis. Boccarelli A., Del Buono N., Esposito F. (2024) International J. of Molecular Sciences. 25(8): 4406. doi: 10.3390/ijms25084406.
Defining a Metacolor Space Representation to Perform Image Segmentation. C. Castiello, Del Buono N., Esposito F. (2024) Preprints 2024, 2024020140. doi: 10.20944/preprints202402.0140.v1.
2023
Reversal of MYB-dependent suppression of MAFB expression overrides leukaemia phenotype in MLL-rearranged AML. Negri A., Ward C. [...], Gargano G., [...]. (2023) Cell Death & Disease 14, 763. doi: 10.1038/s41419-023-06276-z.
Theoretical Aspects in Penalty Hyperparameters Optimization. Esposito F., Selicato L., Sportelli C. (2023) Mediterranean Journal of Mathematics 20 (6), 300. doi: 10.1007/s00009-023-02497-w.
A 16-gene signature reflecting tumor microenvironment predicts the risk of multiple myeloma patients treated by bortezomib-based therapies. Gargano G., [...], Del Buono N., Esposito F. (2023) Clinical Lymphoma, Myeloma and Leukemia 23: S251-S252. doi: 10.1016/S2152-2650(23)02001-3.
Improving Color Image Binary Segmentation Using Nonnegative Matrix Factorization, Castiello C., Del Buono N., Esposito F., (2023) vol 14108 Lecture Notes in Computer Science series. In: Computational Science and Its Applications – ICCSA 2023 Workshops. ICCSA 2023. Lecture Notes in Computer Science, vol 14108. doi:10.1007/978-3-031-37117-2_42.
Bi-level algorithm for optimizing hyperparameters in penalized nonnegative matrix factorization. Del Buono N., Esposito F., Selicato L., R. Zdunek, (2023) Applied Mathematics and Computation, Volume 457, 15 November 2023, 128184. doi: 10.1016/j.amc.2023.128184
Effect of preoperative music therapy versus intravenous midazolam on anxiety, sedation and stress in stomatology surgery: a randomized controlled study. Giordano F., [...], Selicato L., [...]. (2023) Journal of Clinical Medicine. 12(9), 3215. doi: 10.3390/jcm12093215
A Decision-tree Approach to Stratify DLBCL Risk Based on Stromal and Immune Microenvironment Determinants. Zaccaria G.M., [...], Esposito F., Gargano G., et al. In HemaSphere 7.4 (2023): e862. doi: 10.1097/HS9.0000000000000862.
Detecting Anomalies in Marine Data: A Framework for Time Series Analysis. Del Buono N., Esposito F., Gargano G., Selicato L., Taggio N., Ceriola G., and Iasillo D. (2023). In Machine Learning, Optimization, and Data Science. LOD 2022. Lecture Notes in Computer Science, vol 13810, pp. 485–500. Springer, Cham. doi:10.1007/978-3-031-25599-1_36.
Machine Learning Approaches for Predicting Crystal Systems: A Brief Review and a Case Study. Settembre G., Corriero N., Del Buono N., Esposito F., and Rizzi R. (2023). In Machine Learning, Optimization, and Data Science. LOD 2022. Lecture Notes in Computer Science, vol 13810, pp. 93-107. Springer, Cham. doi:10.1007/978-3-031-25599-1_8.
Cluster of resistance-inducing genes in MCF-7 cells by estrogen, insulin, methotrexate and tamoxifen extracted via NMF. Boccarelli A., Del Buono N., and Esposito F. In Pathology, research and practice 242 (2023): 154347. doi:10.1016/j.prp.2023.154347.
CrystalMELA: a new crystallographic machine learning platform for crystal system determination. Corriero N., Rizzi R., Settembre G., Del Buono N., and Diacono D. In Journal of Applied Crystallography (IUCr), vol. 65, no. 2. doi:10.1107/S1600576723000596.
2022
Soil Moisture Sensor Information Enhanced by Statistical Methods in a Reclaimed Water Irrigation Framework. Giorgio A., Del Buono N., Berardi M., Vurro M., Vivaldi G.A. In Sensors 2022, 22(20), 8062. doi:10.3390/s22208062
Role of lipidomics in assessing the functional lipid composition in breast milk. Ganeshalingam M, Enstad S, Sen S, Cheema S, Esposito F and Thomas R (2022) Front. Nutr. 9:899401. doi: 10.3389/fnut.2022.899401
NR1H3 (LXRα) is associated with pro-inflammatory macrophages, predicts survival and suggests potential therapeutic rationales in diffuse large b-cell lymphoma. Vegliante, MC, Mazzara, S, Zaccaria, GM, De Summa, S, Esposito, F,...,Gargano, G, et al. Hematol Oncol. 2022; 1- 12. https://doi.org/10.1002/hon.3050
Colorectal cancer in Crohn's disease evaluated with genes belonging to fibroblasts of the intestinal mucosa selected by NMF. Boccarelli A., Del Buono N., and Esposito F.. Pathology-Research and Practice 229 (2022): 153728. https://www.sciencedirect.com/science/article/pii/S0344033821003897
Bi-level Optimization for hyperparameters in Nonnegative Matrix Factorizations. Del Buono N, Esposito F., Selicato L., Zdunek R. arXiv preprint arXiv:2203.13129 (2022).
2021
A New Ensemble Method for Detecting Anomalies in Gene Expression Matrices, Selicato, L.; Esposito, F.; Gargano, G.; Vegliante, M.C.; Opinto, G.; Zaccaria, G.M.; Ciavarella, S.; Guarini, A.; Del Buono, N. Mathematics 2021, 9, 882. https://doi.org/10.3390/math9080882
Anomalies detection in gene expression matrices: Towards a new approach. Del Buono N., Esposito F., Selicato L., Vegliante MC. 12th International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2021-Part of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2021. SciTePress, 2021.
Low rank approaches for the analysis of real data from pre to post processing. Esposito F., Selicato L., Del Buono N., PROCEEDINGS OF SIMAI 2020+ 21 (2021).
A Review on Initialization Methods for Nonnegative Matrix Factorization: Towards Omics Data Experiments, Esposito, F. Mathematics 2021, 9, 1006. https://doi.org/10.3390/math9091006
Toward a New Approach for Tuning Regularization Hyperparameter in NMF, Del Buono N., Esposito F., Selicato L. In: Nicosia G. et al. (eds) Machine Learning, Optimization, and Data Science. LOD 2021. Lecture Notes in Computer Science, vol 13163. Springer, Cham. https://doi.org/10.1007/978-3-030-95467-3_36
Electronic case report forms generation from pathology reports by ARGO, automatic record generator for onco-hematology. Zaccaria, G.M., Colella, V., Colucci, S., Clemente F., Pavone F., Vegliante MC, Esposito F. et al. Sci Rep 11, 23823 (2021). https://doi.org/10.1038/s41598-021-03204-z
Analysis of fibroblast genes selected by NMF to reveal the potential crosstalk between ulcerative colitis and colorectal cancer. Boccarelli A, Del Buono N., and Esposito F.. Experimental and Molecular Pathology 123 (2021): 104713.
Nonnegative Matrix Factorization models for knowledge extraction from biomedical and other real world data, F. Esposito, N. Del Buono, and L. Selicato, PAMM 20.1 (2021): e202000032.
2020
Methods for Hyperparameters Optimization in Learning Approaches: an overview, N. Del Buono, F. Esposito and L. Selicato, International Conference on Machine Learning, Optimization, and Data Science LOD2020, LNCS, 2020.
Hybrid projective Nonnegative Matrix Factorization based on $\alpha$-Divergence: Image Feature Extraction and Data Clustering, M.T. Belachew, N. Del Buono, Applied Mathematics and Computation, Vol 369, 15 March 2020, doi :10.1016/j.amc.2019.124825
An NMF-Based Methodology for Selecting Biomarkers in the Landscape of Genes of Heterogeneous Cancer-Associated Fibroblast Populations. F. Esposito, Boccarelli A, N. Del Buono. Bioinformatics and Biology Insights. January 2020. doi:10.1177/1177932220906827
The influence of music therapy on preoperative anxiety in pediatric oncology patients undergoing invasive procedures. F. Giordano; B. Zanchi; C. Rutigliano; F. De Leonardis; F. Esposito; N. Brienza; N. Santoro, The Arts in Psychotherapy, Volume 68, 101649,https://doi.org/10.1016/j.aip.2020.101649 , ISSN: 0197-4556, 2020.
2019
Orthogonal Joint Sparse NMF for Microarray Data Analysis, N. Del Buono, F. Esposito, N. Gillis, Journal of Mathematical Biology, 79: 223. https://doi.org/10.1007/s00285-019-01355-2 ISSN: 0303-6812, 2019
Investigating initialization techniques for Nonnegative Matrix Factorization: a survey and a case of study of microarrays, N. Del Buono e F. Esposito, Series in Applied Sciences: Volume 2. Mathematical Modelling, Numerical and Data Analysis, ISBN 978-88-3369-044-5, 2019.
Nonnegative Matrix Factorizations for Knowledge Extraction from Biomedical and other real world data. F. Esposito, Department of Computer Science, University of Bari Aldo Moro, Italy PhD thesis
2018
On some practical issues related to Nonnegative Matrix Factorization in Microarray Data Analysis context, N. Del Buono and F. Esposito, Series in Applied Sciences: Volume 1. Mathematical Modelling, Numerical and Data Analysis, pag 109-130, ISBN 978-88-3369-044-5 ,doi: 10.17605/OSF.IO/KR2J3 , 2018
Improving knowledge on the activation of bone marrow fibroblasts in MGUS and MM disease through the automatic extraction of genes via a Nonnegative Matrix Factorization approach on gene expression profiles, A. Boccarelli, F. Esposito, N. Del Buono, A. Vacca, M. Coluccia, Journal of Translational Medicine Journal of translational medicine, 16(1):217https://doi.org/10.1186/s12967-018-1589-1 , ISSN: 1479-5876, 2018.
A Framework for Intelligent Twitter Data Analysis with Nonnegative Matrix Factorization, G. Casalino, C. Castiello, N. Del Buono, C. Mencar, International Journal of Web Information Systems, 2018, doi: 10.1108/IJWIS-11-2017-0081 , 2018
Tri-orthogonal NMF for monitoring the upwelling phenomenon using Sentinel-3 products. F. Esposito, K. Karamvasis, V. Karathanassi, N. Del Buono, Technical Report 10/2018, Department of Mathematics, University of Bari.
2017
Intelligent Twitter Data Analysis based on Nonnegative Matrix Factorizations, G. Casalino, C. Castiello, N. Del Buono, C. Mencar, O. Gervasi et al. (Eds.): ICCSA 2017, Part I, LNCS 10404, 2017, DOI: 10.1007/978-3-319-62392-4_14
Q-matrix Extraction from Real Response Data Using Nonnegative Matrix Factorizations, G. Casalino, C. Castiello, N. Del Buono, F. Esposito, C. Mencar, O. Gervasi et al. (Eds.): ICCSA 2017, Part I, LNCS 10404, 2017,DOI: 10.1007/978-3-319-62392-4_15 , ISSN: 0302-9743, 2017
HLA data analysis in patients affected by kidney diseases and comparison with healthy subjects, N. Del Buono, F. Esposito, C. Castiello, M. Margiotta, Rapporto del Dipartimento di Matematica n.6 del 08.06.2017.
2016
Breast cancer’s microarray data: pattern discovery using Nonnegative Matrix Factorizations, N. Del Buono, F. Esposito, F. Fumarola, A. Boccarelli, and M. Coluccia, LCNS, Second International Workshop on Machine learning, Optimization and big Data - MOD 2016 , Editors: G. Giuffrida, G.Nicosia, P.Pardalos, LNCS, 10122, Springer,DOI: 10.1007/978-3-319-51469-7_24 ISSN: 0302-9743, 2016