The IBI group led by Ferran Sanz and Laura I. Furlong, promotes and tackles synergistic and integrative strategies for facing biomedical problems by making use of approaches developed at the IBI group and by fostering the collaboration between research groups of the GRIB.
Currently, an increasing wealth of information, particularly the one generated by biomedical research, is left unused. There is a great difficulty in both the identification and use of clinically actionable information. The goal of our group is to advance biomedical discovery and have an impact in pharmaceutical industry and health care by applying text mining and knowledge management, network biology and real world data analytics. In our research we use different type of data, such as free text (e.g. publications), omics data, patient-level data (from Electronic Health Records), and apply a variety of methods encompassing statistics and machine learning, natural language processing and text mining, network and systems biology. Another important aspect of our group is that we provide several services to the community, such as databases and analytical tools.
The current research lines of the Integrative Biomedical Informatics are:
- Text mining
- Knowledge management and linked data
- Network medicine
- Real World Data (RWD) analytics in health