Endometriomicsin silico data mining of omics studies in endometriosis
- Francisco José Esteban Ruiz Director/a
- Signe Altmäe Codirector/a
Universidad de defensa: Universidad de Jaén
Fecha de defensa: 01 de julio de 2021
- Patricia Díaz Gimeno Presidente/a
- Santos Blanco Ruiz Secretario
- Maire Peters Vocal
Tipo: Tesis
Resumen
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.