Transforming biology into a quantitative and interdisciplinary science requires researchers who are able to connect deep biological understanding with the ability to apply mathematical tools as well as theoretical concepts of physics, enigineering, and computer science. Traditionally, students of biology or biochemistry have only little education in these quantitative sciences, and physical science students miss to learn about the details of complex biological structures and processes. However, even if courses on computational biology are offered, education is usually one-sided, focussing either on statistical analysis of large data sets or on mathematical modelling of dynamical properties of cellular processes. I will discuss experiences from a Masters curriculum and a Research Training Programs recently established at Humboldt University trying to integrate these two complementary approaches for a quantitative understanding of cellular structures and functions. I will demonstrate how the student can benefit very much from simultaneously applying methods of bioinformatics and methods of mathematical modelling to one and the same systems, for example, a metabolic network or a signal transduction network. I will also show how our educational program benefits from close international cooperation including exchange of students and teachers as well as joint research projects.