- Marta Villegas
- Aitor González
- Ander Intxaurrondo
- Jesús Santamaría
CNIO and the State Secretariat for Telecommunications and the Information Society (SETSI) are collaborating on the identification and development of Text and Data mining resources to transform the growing amount of key health information hidden in electronic health records, scholarly communications, patents or social media into structured data of practical utility in the clinic, as well as for basic biomedical research. The integration of results from clinical and biomedical text mining systems with bioinformatics infrastructures is critical to empower precision medicine approaches that enable a more comprehensive and systematic understanding of the molecular characteristics of cancer patients. Our Unit is funded through an ‘encomienda’ between the SETSI and CNIO as part of the 90 million Euro Strategic National Plan for the Advancement of Language Technologies. The mission of the Unit is to characterise the state-of-the-art of clinical text mining systems, provide assistance to adapt and apply clinical text mining components to various use cases and to generate key resources including components, annotated data and evaluation infrastructures.
- Information Retrieval and Text Mining Technologies for Chemistry.(2017)
Chem Rev 117, 7673-7761.
- A molecular hypothesis to explain direct and inverse co-morbidities between Alzheimer’s Disease, Glioblastoma and Lung cancer.(2017)
Sci Rep 7, 4474-.
- LimTox: a web tool for applied text mining of adverse event and toxicity associations of compounds, drugs and genes.(2017)
Nucleic Acids Res (in press).