The goal of the course is to guide students through the essential aspects of molecular neuroscience and neurodegenerative diseases. The student will gain the ability to dissect the molecular basis of disease in the nervous system in order to begin to understand and identify therapeutic strategies.
"In silico Neuroscience" introduces students to a synthesis of modern neuroscience and state-of-the-art data management, modelling and computing technologies.
Neuroengineering is at the frontier between neuroscience and engineering: understanding how the brain works allows developing engineering applications and therapies of high impact, while the design of new measurement and data analysis techniques contributes to advance our knowledge about the brain.
This course introduces the student to the fudamentals of pharmacology, pharmacokinetics and drug-receptor interactions. It discusses also pharmacogenetics and chronopharmacology, to exemplify the challenges of personalized medicine.
Biochemistry is a key discipline for the Life Sciences. Biological Chemistry I and II are two tightly interconnected courses that aim to describe and understand in molecular terms the processes that make life possible.
The course covers the fundaments of bioelectronics and integrated microelectronics for biomedical and implantable systems. Issues and trade-offs at the circuit and systems levels of invasive microelectronic systems as well as their eluding designs, methods and classical implementations are discussed
Basic course in biochemistry as well as cellular and molecular biology for non-life science students enrolling at the Master or PhD thesis level from various engineering disciplines. It reviews essential notions necessary for a training in biology-related engineering fields.
Presentation of selected signalling pathways with emphasis on both the mechanism of action of the molecules involved, molecular interactions and the role of their spatio-temporal organization within the cell, considering cellular dimensions and conditions.
The course covers in detail molecular mechanisms of cancer development with emphasis on cell cycle control, genome stability, oncogenes and tumor suppressor genes.
Computer modelling is increasingly used to study dynamic phenomena in cell biology. This course shows how to identify common mathematical features in cell biological mechanisms, and become proficient in selecting numerical algorithms to model them and predict their behaviour.
