Copula Graphical Modeling of Proteomic Data in Thyroid Lesions
Marta Nesteruk
Copula Graphical Modeling of Proteomic Data in Thyroid Lesions.
Rel. Enrico Bibbona, Giulia Capitoli. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Matematica, 2025
|
Preview |
PDF (Tesi_di_laurea)
- Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives. Download (5MB) | Preview |
Abstract
Thyroid nodules are a common occurrence in the general population, yet preoperative assessment of malignancy often remains inconclusive. This uncertainty can lead to surgical decisions that later may prove unnecessary. Identifying potential molecular biomarkers could refine diagnosis and support more informed care. In this setting, proteomic profiling with Matrix Assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) has shown promise for characterizing tissue at the molecular level. This thesis presents a comparative statistical study of MALDI-MSI proteomic data from thyroid biopsies classified into five diagnostic categories: Follicular Adenoma, Hürthle Cell Adenoma, Papillary Thyroid Carcinoma (PTC), Follicular Variant of Papillary ThyroidCarcinoma (FVPTC), and Noninvasive Follicular Thyroid Neoplasm with Papillary-like Nuclear Features (NIFTP), a recently defined and diagnostically challenging entity.
The analysis compares univariate and multivariate statistical approaches to explore molecular differences between diagnostic groups
Tipo di pubblicazione
URI
![]() |
Modifica (riservato agli operatori) |
