Sile: a method for the efficient management of smart genomic information
- Autores: Ana León Palacio
- Directores de la Tesis: Oscar Pastor López (dir. tes.)
- Lectura: En la Universitat Politècnica de València ( España ) en 2019
- Idioma: español
- Tribunal Calificador de la Tesis: Juan Trujillo Mondéjar (presid.) , Maribel Yasmina Campos Alves Santos (secret.) , Jolita Ralyté (voc.)
- Enlaces
- Tesis en acceso abierto en: RiuNet
- Resumen
In the last two decades, the data generated by the Next Generation Sequencing Technologies have revolutionized our understanding about the human biology. Furthermore, they have allowed us to develop and improve our knowledge about how changes (variants) in the DNA can be related to the risk of developing certain diseases.
Currently, a large amount of genomic data is publicly available and frequently used by the research community, in order to extract meaningful and reliable associations among risk genes and the mechanisms of disease. However, the management of this exponential growth of data has become a challenge and the researchers are forced to delve into a lake of complex data spread in over thousand heterogeneous repositories, represented in multiple formats and with different levels of quality. Nevertheless, when these data are used to solve a concrete problem only a small part of them is really significant. This is what we call "smart" data.
The main goal of this thesis is to provide a systematic approach to efficiently manage smart genomic data, by using conceptual modeling techniques and the principles of data quality assessment. The aim of this approach is to populate an Information System with data that are accessible, informative and actionable enough to extract valuable knowledge.
