Description:

Mass spectrometry based proteomic experiments generate ever larger datasets and, as a consequence, complex data interpretation challenges. In this course, the concepts and methods required to tackle these challenges will be introduced, covering peptide and protein identification, quantification, and differential analysis. Moreover, more advanced experimental designs and blocking will also be introduced. The core focus will be on shotgun proteomics data, and quantification using label-free precursor peptide (MS1) ion intensities. The course will rely exclusively on free and user-friendly software, all of which can be directly applied in your lab upon returning from the course. You will also learn how to submit data to PRIDE/ProteomeXchange, which is a common requirement for publication in the field, and how to browse and reprocess publicly available data from online repositories. The course will thus provide a solid basis for beginners, but will also bring new perspectives to those already familiar with standard d ata interpretation procedures in proteomics. Note: This is a highly interactive course. It requires that the participants interact with each other and with the course instructors, in order to reach the learning outcomes in full.

Start: Monday, 12 September 2022 @ 09:30

End: Friday, 16 September 2022 @ 18:30

Timezone: Lisbon

Venue: Instituto Gulbenkian de Ciência

City: Oeiras

Country: Portugal

Postcode: 2780-156

Eligibility:
  • Registration of interest

Organizer: Pedro Fernandes

Contact: bicourses@igc.gulbenkian.pt

Host institutions: Instituto Gulbenkian de Ciência

Keywords: Proteomics

Target audience:
  • PhD Students
  • Biologists and bioinformaticians who are dealing with high-throughput gene expression data or other high-throughput data and would like to learn state-of-the-art methods for mining and analysing such data.
  • post-doctoral researchers and principle investigators working in wet-lab biology. Participants who are looking for a basic introduction to the bioinformatics resources offered by the EMBL-EBI and want to know more about accessing biological data and tools.
  • computational and statistical techniques are used to identify and validate the causal links between targets

Capacity: 20

Event type:
  • Workshops and courses

Sponsors: Oeiras Valley