The Zurich Seminars in Bioinformatics series is a year-round series of seminars where members of bioinformatics groups in the Zurich area as well as external guests present a variety of research and infrastructure projects loosely representing "Bioinformatics".
The seminar takes place on Thursdays between 12:15 and 13;00 on Irchel campus. If you're interested to attend or present please contact Michael for more information.
The “BIO390” lecture series at the University of Zurich runs through the Autumn semester, with once per week 2h lectures, in each ow which a different aspect of bioinformatics is being presented by a specialist in the respective field. Please visit the website for further information.
The handling and analysis of biological data using computational methods has become an essential part in most areas of biology. In this lecture, students will be introduced to the use of bioinformatics tools and methods in different topics, such as molecular resources and databases, standards and ontologies, sequence and high performance genome analysis, biological networks, molecular dynamics, proteomics, evolutionary biology and gene regulation. Additionally, the use of low level tools (e.g. Programming and scripting languages) and specialized applications will be demonstrated. Another topic will be the visualization of quantitative and qualitative biological data and analysis results.
The “BIO392” block course at the University of Zurich runs through the first weeks of the Autumn semester. The course’s focus is on the practical exploration of software tools and resources related to the analyses of biological sequences, with a focus on human genomic and proteomic variants.
Please visit the website for further information.
One of the fastest growing areas of bioinformatics is in the analysis, warehousing and representation of genomic and protein sequence variants, particularly with view on the use of molecular data in personalised health and biomedical applications in general. This course will engage participants to explore common data formats, online resources and analysis techniques, with a focus on human genome variation data.