Poster Open Access
Mathis, Roland; Manica, Matteo; Martinez Rodriguez, Maria
Motivation: Prostate cancer is a leading cause of cancer death amongst men, however the molecular-level understanding of disease onset and progression are largely unknown. Specifically, stratification of intermediate prostate tumor states based
on current markers is difficult. To improve stratification we (1) integrate data, literature and public databases, (2) extract interaction groups from interactome and cluster patients for each interaction group, (3) train a classifier using the patient profiles to identify marker interactions.