Group Stubbs

Artificial Intelligence (AI) in Healthcare
Machine learning (ML) techniques are used to deliver predictive models form multi-omics experiments, in translational and clinical research projects.  ML methods have been used for discriminating bacteria from viral infections and are used improve patient stratification is pancreatic cancer patients (Eurostars iKnowIT grant).  We have integrated these ML techniques into an open source a predictive modelling application (JUNIPER).  In 2018 we extended our AI portfolio to include deep learning protocols including neural networks to improve patient stratification prediction.

Translational Bioinformatics
We implement reusable strategies and software directed at solving clinically relevant problems in cancer, immunology, cardiovascular disease and clinical genetics at Erasmus MC.  We are the Dutch co-lead for the European Galaxy project which is the EU standard platform for bioinformatics analysis.  We have implemented three Galaxy servers all aspects of bioinformatics supporting Cancer research, antigen predication, metagenomics and neo-antigen prediction

Molecular Diagnostics
We have developed MolDia a secure reporting platform for molecular diagnostics.  We deliver image analysis (e.g. automated hotspot detection) and to somatic variation predictions using the Galaxy platform.      

FAIR Data management & Analysis
FAIR data management is required by all H2020 projects.  To address this requirement, we have developed cloud based FAIR data management and analysis platform.  This myFAIR-CLOUD forms the basis for the development of clinical mining platform for the Canada-European Big Data Federated analysis (CINECA) H2020 project and for pancreatic cancer decision support (iKnowIT).

• ELIXIR: Galaxy Community
• ELIXIR: myFAIR Analysis
• ZonMw: MolDia2All: Diagnostic Reporting Service for Molpath 
  

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  A.P. (Andrew) Stubbs, Associate Professor

  Principal investigator