Endometriomicsin silico data mining of omics studies in endometriosis

  1. Vargas Liébanas, Eva
Dirigida por:
  1. Francisco José Esteban Ruiz Director/a
  2. Signe Altmäe Codirector/a

Universidad de defensa: Universidad de Jaén

Fecha de defensa: 01 de julio de 2021

Tribunal:
  1. Patricia Díaz Gimeno Presidente/a
  2. Santos Blanco Ruiz Secretario
  3. Maire Peters Vocal

Tipo: Tesis

Teseo: 680094 DIALNET lock_openRUJA editor

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.