EMBL Courses and Conferences during the Coronavirus pandemic
With the onsite programme paused, many of our events are now being offered in virtual formats.
Registration is open as usual for many events, with back-up plans in place to move further courses and conferences online as necessary. Registration fees for any events affected by the COVID-19 disruption are fully refundable.
More information for participants of events at EMBL Heidelberg can be found here.
Systems biology is a still expanding field of research aiming to understand at the molecular level how cells, tissues and organism operate in their biological context. Among the key technologies driving this forward are next-generation sequencing and proteomics, as they provide powerful means to determine globally expression levels of genes and proteins. Both fields have matured to a degree that they have now become accessible to researchers in many areas of biology.
This course is targeted at biologists and biochemists who are (or starting to be) involved in both next-generation sequencing and mass spectrometry-based proteomics, but who are not experts in these fields.
- Protein quantification
- Next generation transcriptome and mass spectrometrey-based proteome data analysis
- Bioinformatics tools for transcriptome and proteome data mining
- Understanding experimental parameters (resolution, mass accuracy, peak shape, fragmentation)
The aim of this practical course is to provide insight in techniques that are frequently used for transcriptome and proteome analysis, and to provide hands-on experience turning primary data into information that can be used for further biological interpretation. To achieve these aims, we'll provide participants with next generation transcriptome and mass spectrometry-based proteome data that has been acquired at EMBL on stem cells and differentiated cells, serving as a central theme throughout the course to provide overall coherence. These data will be used to provide insight into metrics to assess data quality, to be trained in the use of available bioinformatic tools for data interpretation, and to get insight in the complementarity of transcriptome and proteome data and ways to integrate them.