Quantitative Biology (Classe LM-8)-Enrolled from 2020/2021 Academic Year

The Master's degree course in Quantitative biology (QB) prepares graduates in biological and biotechnological disciplines to operate at the intersection between biology and physics. The quantitative approach requires a physical understanding of biological phenomena and the development of mathematical and computational tools for the analysis, understanding, and redesign of biological systems. The aim is to train a new generation of experts with integrated skills in biology, chemistry, physics, mathematics and computer science, able to perform accurate experimental measurements and apply predictive theoretical models, to explain biological complexity. Quantitative biology uses emerging technological and computational capabilities to model biological processes for biotechnological applications such as protein and metabolic engineering, drug discovery and synthetic biology. It is therefore proposed a path that includes training activities aimed at acquiring in-depth knowledge of:

(a) biochemical and biophysical aspects of cellular processes and molecular interactions;

(b) experimental methodologies for the study and measurement of these processes;

(c) analytical techniques and protocols used in structural biology and molecular and cellular biophysics studies;

(e) technical bases of modelling in systems biology for the study of interactions in complex biological systems;

(f) linear algebra, matrix calculus and its use in the description of dynamic biological phenomena and to understand the basis of artificial intelligence (machine learning);

(g) Python programming language and its use for statistical data analysis;

(h) formal logic elements

Characteristic and related mandatory teachings (72 CFU, of which 6 CFU with guided choice) include teachings on quantitative aspects of the main molecular and cellular biological disciplines, teachings on chemistry involving spectroscopy and its applications in biology; aspects of statistical analysis of data and errors, measurements of nanoscale interactions between biomolecules, programming elements in Python and machine learning aspects, linear and matrix algebra, description of dynamic systems using differential equations.

In addition, 12 CFU will be freely chosen by the students from among all the teachings activated by the University of Milan, provided they are consistent with the training project and 3 CFU for other activities (Italian language skills for foreigner students or seminars and orientation to the world of work).

Finally, the course includes, as a qualifying moment of training and acquisition of skills, an experimental thesis lasting at least 33 CFU. The Thesis Internship must be carried out in research laboratories of the University of Milan or in other public or private institutions, national or foreign, after approval, and provides for the production of a written thesis, in which the original results of the research are reported.