Publications

List of publications related to the project:

• 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.

• Penalty hyperparameter optimization with diversity measure for nonnegative low-rank approximation. N. Del Buono, F. Esposito, L. Selicato, and R. Zdunek (2024). Applied Numerical Mathematics, Elsevier BV. doi: 10.1016/j.apnum.2024.10.002

• A network-constrain Weibull AFT model for biomarkers discovery. C. Angelini, D. De Canditiis, I. De Feis, A. Iuliano. in Biometrical Journal (2024). https://doi.org/10.1002/bimj.202300272

•  INet for network integration, V. Policastro, M. Magnani, C. Angelini, A. Carissimo. in Computational Statistics (2024).https://doi.org/10.1007/s00180-024-01536-8

• Accelerated SVD-based initialization for nonnegative matrix factorization. F. Esposito, S.M Atif, N. Gillis, N. in Computational Applied Mathematics, 43, 392 (2024). https://doi.org/10.1007/s40314-024-02905-1

• A targeted gene signature stratifying mediastinal gray zone lymphoma into classical HL-like or PMBL-like subtypes. G. Gargano, [...], F. Esposito, [...], N. Del Buono, [...]. Haematologica, Vol. 109 No. 11 (2024), pp. 3771-3775. doi: 10.3324/haematol.2024.285266.

• Penalizing Low-Rank Matrix Factorization: From theoretical connections to practical applications,  N. Del Buono, F. Esposito, L. Selicato, (2025), Journal of Computational Mathematics and Data Science, Elsevier BV. Volume 14, 100111 https://www.sciencedirect.com/science/article/pii/S2772415825000033

• Assess Optimal Penalty Hyperparameters in Nonnegative Matrix Factorization Within Hilbert Spaces Perspective. L. Selicato, F. Esposito (2025). Mediterranean Journal of Mathematics 22 (5), pp. 1-20. doi: 10.1007/s00009-025-02875-6.

• AI-Derived Five-Gene Signature Predicts Risk in Multiple Myeloma under Bortezomib-Based Therapy. G. Gargano,[...], F. Esposito, [...] N. Del Buono, [...], S. Ciavarella. (2025). Scientific Reports. doi:10.1038/s41598-025-30527-y.

• Analyzing Complex Breastmilk Lipidomics Data Using Nonnegative Matrix Factorization as a Parsimonious Data Reduction TechniqueM. Ganeshalingam, F. Esposito,  [...], N. Del Buono, et al., (2025), under revision for Analytical Chemistry.

• Sparse Hyperparametric Itakura-Saito NMF via Bi-Level Optimization. L. Selicato, F. Esposito, A. Ang, N. Del Buono, R. Zdunek (2026). Journal of Computational and Applied Mathematics. doi: 10.1016/j.cam.2025.117316.

• G. Gargano, F. Esposito, N. Del Buono, S. Ciavarella, M.C. Vegliante. Identification of differentially expressed genes in RNA-seq data via semi-rigid orthogonal sparse KL-NMTF. BMC Bioinformatics (2026). https://doi.org/10.1186/s12859-026-06370-x