Swiss Proteomics Society, 2004 Congress

Monday 6 December 2004
13:30- 16:20 at Inselspital (Kinderklinik) - Bern

ANALYSING MS DATA

A tutorial will be organised by the Swiss Proteomics Society in collaboration with Roche and the University of Bern. This introductory tutorial in mass spectrometry is addressed to scientists with limited experience. Emphasis will be given to gaining understanding of MS experimental procedures, data production and data analysis, including a short introduction in experimental design and statistical evaluation of MS-gained data.

The programme will consist of the following 2 modules of 1h15 each:

	Introduction to MS data acquisition
13:30 - 14:45	Manfred Heller,Department of Clinical Research, Inselspital, University of Bern Mass spectrometry has become the central tool for protein analysis in proteomics. This introduction is aimed at giving an overview on proteomics and its other ‘omics’ family members. From this it becomes clear why mass spectrometry plays such an important role for ‘omics’ research. Furthermore, we will discuss the different instrument configurations used in mass spectrometry, what they can do for us, and some aspects on the data acquisition and quality.
14:45 - 15:05	COFFEE BREAK
	MS data analysis and interpretation
15:05 - 16:20	Axel Ducret,F. Hoffmann-La Roche Ltd, Basel In the second part of the course we will cover how the mass spectral information can be correlated to the biological information. We will look at popular MS identification algorithms and we will provide a general overview on how to understand the data analysis outputs provided by these software tools. Finally, we will cover some of the general aspects on design of experiment and their implications in the interpretation of MS-based data.

Participation will be limited to 30 persons!

Price: 80 CHF (including coffee break and handouts)

You may register to this Short Course in Proteomics through the Congress Registration Form.

Should you require more information about the course, please contact:

Patricia M. Palagi, Swiss Institute of Bioinformatics, Geneva