pixel José Pereira Leal | Universidade NOVA de Lisboa

José Pereira Leal

José Leal

Contact Mentor

CEO, Ophiomics

Short bio

José Pereira-Leal has a Ph.D. in Biomedical Sciences from the University of Oporto (Portugal), having performed all the thesis research work at the Imperial College School o Medicine (London, UK) and the Southwestern Medical School at Dallas (Texas, USA). His Ph.D. thesis focused on the biochemistry and bioinformatics of proteins involved in genetic diseases. He was a postdoctoral fellow at the EMBL European Bioinformatics Institute and at the Medical Research Council’s Laboratory of Molecular Biology, both in the UK, in the areas of Computational/Systems Biology and Bioinformatics.

After 10 years abroad, he returned to Portugal where he established and coordinated the Computational Genomics Laboratory, supervising post-docs, Ph.D. and MSc students, as well as clinicians, in projects on comparative genomics, medical genomics, and data integration. He also coordinated the Bioinformatics Unit of the Instituto Gulbenkian de Ciência, where he helped establish the European biological data infrastructure ELIXIR, and its national counterpart, the Portuguese biological data infrastructure BioData.pt.

José was the Scientific Director of Healthcare City, an initiative of NOVA Medical School with corporate partners, focused on the support of Healthcare startups.

He is a founder and the executive director of Ophiomics and is committed to translating the latest advances in Genomic and Bioinformatics research to improve clinical practice and patient care.

Main Skills

  • Clinical Diagnostics
  • Genomic
  • Bioinformatics
  • Big data

Areas of interest for mentoring

  • Life Sciences
  • Health

Motivation to be a mentor

  • Enjoyment to support the development of innovative ideas and contribute to the success of new ventures;
  • Personal satisfaction in sharing experiences and know-how.

Availability

  • Face to face
  • Skype (or similar)
Clinical Diagnostics | Genomics | Bioinformatics | Big Data