This seminar will cover central aspects of modern bottom-up proteome analysis by mass spectrometry with a focus on bioinformatic algorithms and data analysis.

No prior knowledge of LC-MS based proteomics is required. All levels of expertise are welcome.

    After a brief introduction to the field of mass spectrometry-based proteomics (instrument types, data properties, overview of bioinformatics challenges) we will explore the big cornerstones, including isotope models and averagines, scoring algorithms for the identification of mass spectra, false-discovery-rate estimation using decoy peptides, absolute and relative quantification of proteins and correlation between mRNA and protein expression.

Attention: The first regular class will take place on Friday, April 19th (=easter), 26th!

Update: please decide on a topic for your talk based on the selection of papers in the Resource section  (ZIP file download) by April 19th and email me (chris.bielow@fu-berlin.de) your choice. First come first serve. Proposing other papers for presentation which fit the scope of the seminar are also welcome. The exact date of student presentations will be decided by end of April.

Confirmed talk topics (list will be updated regularly):

PepNovo: F. Peppert

Kaell (2007): P. Hiort

ProteinProphet: A. Ravishankar

Burger (2017): A. Ravi Shankar

Protein-mRNA Correlations: L. Seshadri

The first two classes will be lectures, introducing mass-spectrometry based-proteomics (instruments, recording modes, properties of data, etc).

From class three onwards we will have student talks on dedicated topics and discussions (critically assessing the merits of the paper and its impact on the field).

The final 1-2 sessions will consist of presentations on the results of the research projects (10-15min each).

Students will:

 - give one presentation on a chosen topic (see Resources for a list of papers/PDFs); additional proposals of topics by students are encouraged

- develop a small research project (usually based on the topic of the presentation) and present the results at the last sessions of the seminar

This seminar will enable to students to:

• present and discuss research concepts and strategies (in a potentially new field of research)
• discuss pro's and con's of existing computational (and experimental) methods
• conduct small original research project of your own (and present/defend it)