Giulia Della Croce Di Dojola
Technical variability versus biological heterogeneity in single-cell RNA-sequencing data.
Rel. Enrico Bibbona, Gianluca Mastrantonio. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Matematica, 2021
|
Preview |
PDF (Tesi_di_laurea)
- Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives. Download (4MB) | Preview |
Abstract
The study of gene expression provides many insights in several biological processes. Indeed, gene expression levels can be intended as "signatures" that characterize the tissues of an organism and allow to understand how they are governed at the molecular level. As a consequence, the monitoring of normal growth, as well as disease development, is made possible. Gene expression levels are directly linked to the abundance of mRNA fragments within a cell, that are therefore used as a quantification tool. One of the main techniques often employed to isolate and sequence the mRNA fragments is single-cell RNA-sequencing. This technique allows to perform cell-specific analyses, thus even addressing more complex tissues, made of different types of cells.
Our analysis focuses on trying to estimate the biological variation given by heterogeneous gene expression levels, in a seemingly homogeneous population of cells
Relatori
Anno Accademico
Tipo di pubblicazione
Numero di pagine
Corso di laurea
Classe di laurea
Aziende collaboratrici
URI
![]() |
Modifica (riservato agli operatori) |
