Research groups

Integrative Biomedical Informatics group of GRIB (IBI)

The huge wealth of biomedical information that is currently available is underused because the difficulties in seeking, integrating, analysing the relevant one. There is also a great difficulty for the identification and use of clinically actionable information. The goal of the Integrative Biomedical Informatics (IBI) group, led by Laura I. Furlong and Ferran Sanz, is to develop computational methods and tools to address these challenges, with the aim of better understanding human health and disease and contributing to the design of more effective and safe therapeutic interventions.

The Integrative Biomedical Informatics group is integrated in the Research Programme on Biomedical Informatics, GRIB. The GRIB is a joint research programme of the Hospital del Mar Medical Research Institute (IMIM) and the Department of Experimental and Health Sciences of the Universitat Pompeu Fabra. The GRIB mission is to develop and apply computational methods and information technologies for a better understanding and prediction of biological phenomena, giving especial emphasis to those related to the human diseases, their prevention, diagnosis and pharmacological treatment. Within the GRIB, the IBI group promotes and tackles synergistic and integrative strategies for affording biomedical problems, making use of approaches developed within the IBI group but also fostering the collaboration between research groups of the GRIB.

The ongoing research lines of the IBI group are:

  • New methods and tools for knowledge extraction and linkage from biomedical literature and other publicly available sources.
  • Development of strategies for the research reuse of clinical data
  • Network biology for the study of human diseases and drug toxicity.
  • Integrative knowledge management and exploitation in drug discovery and development.

Main projects

  • 1.

    TransQST: Translational quantitative systems toxicology to improve the understanding of the safety of medicines

    It´s an european collaborative project funded by the Innovative Medicine Iniciative (IMI2) for the period 2017-2021.

  • 2.

    EMIF: European Medical Information Network

    The EMIF project aims to develop a common information framework of patient-level data that will link up and facilitate access to diverse medical and research data sources, opening up new avenues of research for scientists. To provide a focus and guidance for the development of the framework, the project will focus initially on questions relating to obesity and Alzheimer’s disease. EMIF is a European project funded by IMI.

    http://www.emif.eu/

  • 3.

    MedBioinformatics "Creating medically-driven integrative bioinformatics applications focused on oncology, CNS disorders and their comorbidities"

    Aims to develop useful bioinformatics tools and applications, and autonomously usable for analysing the huge amount of data and knowledge generated in healthcare and biomedical research in order to facilitate translational research and precision medicine. European project funded by H2020 for the period 2015-2018 and coordinated by the IBI group.

    http://www.medbioinformatics.eu/

Website

Institutions

Bioinformatics expertise:

Group Leader:

Laura I. Furlong and Ferran Sanz

PIs

Contact:

Chus Donlo

Bioinformatics services offered

  • PsyGeNET: Psychiatric disorders and Genes association NETwork

    a knowledge platform for the exploratory analysis of psychiatric diseases and their associated genes. PsyGeNET is composed of a database and a web interface supporting data search, visualization, filtering and sharing.

    http://www.psygenet.org

  • DisGeNET

    a discovery platform integrating information on gene-disease associations from several public data sources and the literature. Developed by the IBI group of GRIB, DisGeNET integrates expert-curated databases with text-mined data, and it is one of the largest available repositories of its kind. The new release of DisGeNET contains more than 400,000 gene-disease associations, comprising around 17,000 genes, and more than 15,000 diseases and phenotypes.

    http://www.disgenet.org