BIC-50812 Systems@Work: a toolbox of systems biology

Course

Credits 12.00

Language of instruction:

English

Mandatory knowledge:

MOB-20306, MIB-11306

Assumed knowledge on:

MOB-30306

Contents:

The availability of the primary DNA sequences of organisms has given unprecedented insight into evolution of genomes and the realisation that the building blocks of cells share many common elements. This means that traditional subdivisions between animals, plants and prokaryotes begin to disappear. Another effect is the growing need to integrate experimental details from many areas such as bioinformatics, biochemistry, cell biology, physiology and genetics to translate the DNA blue print into a working, living cell. This has given rise to a new field in biology, called systems biology. The primary goal of the Systems-Toolbox is to provide students a broad experimental overview of this new non-reductional approach to a complex biological problem. Examples are understanding a complex phenotype or finding networks of proteins involved in a biosynthetic or signal transduction pathway;
The course is aimed to deal with a selection of the following topics;
1. bioinformatics approaches to integrate proteomics and genomics data;
2. biochemical analysis and in vivo visualization of protein interactions;
- yeast interaction screens;
- protein interaction assays;
- isolation of protein complexes;
- introducing tagged proteins to visualize protein complexes;
- identification of proteins by LCMS/MS/MALDITOF procedures;
3. isolation and characterization of cloned genes for use in yeast/E.coli expression systems;
4. gene expression;
- RT PCR;
- reporter analysis by fluorescence assays;
5. basics of FRET detection; relation with other methods.

Aims:

The primary aim of Systems@Work is to provide students with an integrated set of advanced tools to determine protein networks carrying out specific tasks at the cell level.
Furthermore, the students should learn to collect background information, to collaborate with other students in a small team. Learn to be involved in several experiments simultaneously, occasionally in different research groups. Finally, documentation and presentation of the results are an integral element.

Activities:

- carry out experiments according to available manuals and protocols;
- perform database and neural network-based searches;
- work as a member of a team.

Examination:

The final mark will be based on theoretical insight in the project and laboratory skills shown during the work, on the quality of the oral presentation and written report of the results of the work.

Literature:

Will be provided during the course.