Computational Cancer Genomics Group

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Post-Doctoral Fellows

  • Seokjin Ham
  • A-Reum Nam

Graduate Students

  • Jaejun Lee
  • Adrián Maqueda
  • Manuel Moradiellos

Technicians

  • Diego Sánchez

Our Group investigates how somatic mutations reshape cancer systems at the protein network level. We define large-scale protein–protein functional associations, including previously underappreciated negative interactions, to quantify mutation-driven network perturbations across more than 1,000 tumours. We integrate subclonal architecture with network propagation to develop AI-based models for treatment response prediction across therapies and cancer types. In parallel, we are establishing deep learning frameworks to predict protein–protein interactions from motif and sequence features, enabling scalable reconstruction of cancer-specific interactomes. Together, our work builds a systems-level platform linking mutation, network dynamics, and therapeutic outcome for precision oncology.

Recent publications

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