Creation of networks for the analysis of disease similarities
- Autores: Eduardo Pantaleón García del Valle
- Directores de la Tesis: Alejandro Rodríguez González (dir. tes.)
, Massimiliano Zanin (codir. tes.) - Lectura: En la Universidad Politécnica de Madrid ( España ) en 2022
- Idioma: inglés
- Enlaces
- Tesis en acceso abierto en: Archivo Digital UPM
- Resumen
The application of computer science to the field of biomedicine over the last few decades has provided experts with powerful tools to advance in the pathogenesis, diagnosis and treatment of diseases, improving patient prognosis and reducing clinical costs. Given the increasing volume of medical information generated by publishers and laboratories, network-oriented computing techniques have proven particularly useful for integrating and analyzing the complex factors associated with disorders. Thus, the so-called network medicine has allowed researchers to improve our understanding of diseases, discovering hitherto hidden similarities through their phenotypic, genetic and metabolic relationships, among others.
With the motivation of contributing to a field as relevant as that of biomedicine through computation and network analysis, this doctoral thesis by compendium aims to delve into the study of complex disease networks and propose new applications in biomedical research. For this purpose, we first carried out a systematic review of the most relevant studies in network medicine in the last decade, extracting a novel compilation of relevant sources and tools. We then applied the acquired knowledge to develop disease network-based solutions to data source interoperability and validation of clinical term extraction tools. The obtained results demonstrated the potential of this technology and provided powerful and intuitive tools for researchers.
This doctoral thesis by compendium comprises three articles published in scientific journals with high impact factor. The publications contribute to fulfill the research goals, developing the same thematic unit sequentially. In this way, the contributions of one publication were used as a basis for the next. The results of the thesis, including the developed solutions, have been published for their use, evaluation and extension in future research, and represent a substantial advance over the state of the art.
