Endometriomicsin silico data mining of omics studies in endometriosis
- Vargas Liébanas, Eva
- Francisco José Esteban Ruiz Director
- Signe Altmäe Co-director
Defence university: Universidad de Jaén
Fecha de defensa: 01 July 2021
- Patricia Díaz Gimeno Chair
- Santos Blanco Ruiz Secretary
- Maire Peters Committee member
Type: Thesis
Abstract
This thesis aims to contribute to the research in endometriosis area using in silico data mining approaches with the purpose of gaining knowledge in the mechanisms leading to endometriosis and identifying putative biomarkers of the disease. Study I summarises the main advances in reproductomics and presents examples of analysis of omics data to serve as a guide in the development of omics analyses; in Study II, a systematic review of the literature on endometriosis and related comorbidities is presented together with an in silico approach, which allowed us to identify putative biomarkers of endometriosis; in Study III, the endometrial mid- secretory transcriptome in endometriosis was evaluated to identify a potential dys-regulation that could contribute to endometriosis-associated infertility. The dys-regulation of important genes and molecular processes was evidenced in women with endometriosis.