BIO-373: Genetics and genomicsThe theoretical part of this course covers classical genetics and contemporary genomics. Because bioinformatics has become important for genomic research, the course also includes practical applications to genomic analyses using Python, including group pro ...
BIO-679: Practical - Suter LabBioluminescence imaging and data analysis Splinkerette PCR (to analyze genomic insertion site of a transgene).
The students will obtain theoretical and practical insight into embryonic stem cell biology and the study of gene expression fluctuations in sin ...
BIO-377: Physiologie par systèmesLe but est de connaitre et comprendre le fonctionnement des systèmes cardiovasculaire, urinaire, respiratoire, digestif, ainsi que du métabolisme de base et sa régulation afin de déveloper une réflection scientifique biomédicale. ...
BIO-204: Labo intégré en sciences de la vie IIAu cours de deux semestres, vous utilisez la biologie moléculaire, la biologie cellulaire ainsi que la biochimie pour cloner un ADNc dans un plasmide d'expression, afin de produire, purifier et caractériser la protéine recombinante. ...
BIO-212: Biological chemistry IBiochemistry 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. ...
BIO-480: Neuroscience: from molecular mechanisms to diseaseThe 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 under ...
BIO-624: Practical - Thomä LabExpression and purification of recombinant proteins are key methods in our lab studying protein machines on a structural level and ways in which they can be reprogrammed by small molecules. In the course, we will express and purify proteins and biophysical ...
BIOENG-399: ImmunoengineeringImmunoengineering is an emerging field where engineering principles are grounded in immunology. This course provides students a broad overview of how engineering approaches can be utilized to study immunology, model immune systems, modulate immune response ...
CH-313: Chemical biologyChemical Biology is an interdisciplinary field using chemical principles and techniques to analyse and manipulate biological systems. It relies on small-molecule chemicals to gain an in-depth understanding of biology, and provides new tools and products ra ...
BIO-471: Cancer biology IThe course covers in detail molecular mechanisms of cancer development with emphasis on cell cycle control, genome stability, oncogenes, tumor suppressor genes, signaling pathways involved in cancer, genomic cancer analysis and rational cancer therapies. ...
ChE-403: Heterogeneous reaction engineeringThe theoretical background and practical aspects of heterogeneous reactions including the basic knowledge of heterogeneous catalysis are introduced. The fundamentals are given to allow the design of multiphase chemical reactors. ...
CH-419: Protein mass spectrometry and proteomicsIn systems biology, proteomics represents an essential pillar. The understanding of protein function and regulation provides key information to decipher the complexity of living systems. Proteomic technology now enables deep quantitative proteome mapping v ...
COM-490: Large-scale data science for real-world dataThis hands-on course covers tools and methods used by data scientists, from researching solutions to scaling prototypes on Spark clusters. Students engage with the full data engineering and data science pipeline, from data acquisition to extracting insight ...
PHYS-423: Plasma IFollowing an introduction of the main plasma properties, the fundamental concepts of the fluid and kinetic theory of plasmas are introduced. Applications concerning laboratory, space, and astrophysical plasmas are discussed throughout the course. ...
MICRO-455: Machine learning IReal-world engineering applications must cope with a large dataset of dynamic variables, which cannot be well approximated by classical or deterministic models. This course gives an overview of methods from Machine Learning for the analysis of non-linear, highly noisy and multi dimensional data
BIO-341: Dynamical systems in biologyLife is non-linear. This course introduces dynamical systems as a technique for modelling simple biological processes. The emphasis is on the qualitative and numerical analysis of non-linear dynamical models. Examples are taken from biology and population ...
BIO-603(LG): Practical - LaManno LabGive students a feel for how single-cell genomics datasets are analyzed from raw data to data interpretation. Different steps of the analysis will be demonstrated and the most common statistical and bioinformatic techniques applied by the students. Data an ...
