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Full NameProfessor Walter Kolch

Department:School of Medicine

Organisation:University College Dublin

Email Address:Email hidden; Javascript is required.

Research Fields

  • genetics, genomics and molecular biology
  • cancer/oncology

Postgrad Medical Specialties

  • Medicine
  • Paediatrics
  • Pathology

Medical Subspecialties

  • Haematology
  • Oncology

My Work

Systems Biology Ireland (SBI) combines both experimental and computational research under one roof giving rise to a vibrant and productive interdisciplinary culture. Since its inception in 2009 SBI has grown to comprise >70 staff from >20 different nations producing ~1 publication per week in highly ranked journals including Nature, Cell, Molecular Cell, Cell Reports, Nature Cell Biology, Nature Biotechnology. SBI was rated amongst the top 5 Systems Biology Institutes worldwide by an international peer review panel in November 2014.

SBI develops new precision oncology approaches based on predictive computational modelling. For this we use modern omics technologies to map the components of biological and biochemical networks, and computational modelling to reconstruct these networks and analyse their properties. The resulting predictive models are then personalised using patient data and used for the accurate stratification of patients and for designing personalised therapies.

Potential Projects

Title: Predicting drug resistance in neuroblastoma.

We have previously shown that personalised computational models can accurately stratify neuroblastoma (NB) patients (Fey et al. Signaling pathway models as biomarkers: Patient-specific simulations of JNK activity predict the survival of neuroblastoma patients. Science Signaling 8, ra130, 2015). In collaboration with Our Lady's Children's Hospital, Crumlin, we now want to build on this work and develop models that can predict who will respond to chemotherapy treatment. This project will use patient material to map critical network components and in close interaction with computational modellers design and analyse the personalised patient models. This project is ideally suited for somebody who has a strong interest in paediatric oncology and omics technologies and who has a truly interdisciplinary mindset.