Saskia Haupt and Vincent Heuveline
While the understanding of cancer development has dramatically increased during the last years, key questions with immediate implications for clinical management and prevention strategies remain still unanswered. Mathematical oncology helps answering these questions by using mathematical modeling approaches. It incorporates different aspects: First, the increasing amount of molecular data, particularly whole genome and exome data, provide new possibilities that allow studying the evolution and biology of tumors at an unprecedented accuracy and variability. However, managing this huge amount of data requires dedicated mathematical techniques. Furthermore, mathematical models can be used to evaluate hypotheses about tumor evolution, which in turn can be used to analyze and optimize different clinical approaches including tumor prevention, diagnosis and treatment.