SSC11 home//Preconference courses

SSC11, June 8 -11, 2009

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Symposium secretariat

Tarja Rajalahti

Department of Chemistry,
University of Bergen

Address: Realfagbygget, Allegaten 41
N-5007 Bergen, Norway

Preconference courses, registration is closed

Monday June 8, 2009 (08:30 - 15:00) at Hotel Alexandra

3600 NOK (regular rate)
1800 NOK (students)

Accommodation with buffet dinner on Sunday evening and breakfast and buffet lunch on Monday is NOK 1540 for single room at Alexandra Hotel and NOK 1440 at Hotel Loenfjord.

1. Data integration

Lecturer: Dr. Juergen von Frese. Data Analysis Solutions DA-Sol GmbH, Germany

Data integration is about a systematic, joint analysis of data from different sources (measurement approaches) aiming to harvest their synergy. This can be used advantageously e.g. in biomedical research and diagnostics, drug development or Process Analytical Technology. The course will present a holistic picture of data integration, ranging from the principles and an overall workflow to a discussion of the analytical options and approaches. It will try to provide a systematic, conceptual understanding of the major issues, pitfalls and chances. Besides known chemometric approaches, it will also present and discuss complementary methods from machine learning and pattern recognition.

Download a full course description here :::>


+47 555 83366

+47 555 89490


2. An introduction to multi-way analysis

Lecturer: Prof. Rasmus Bro, University of Copenhagen, Denmark.,

In this course, an introduction is given to multi-way analysis. The basic multi-way models are explained in simple manners and it is shown how they can be used to extract more information from e.g. data from chromatographic analysis, fluorescence spectroscopy, sensory data and high and low-field NMR spectroscopy. Basic models such as PARAFAC, PARAFAC2, Tucker3 and multi-way PLS are explained and examples will be given on how to use these in MATLAB using either PLS_Toolbox or the free N-way toolbox. There will also be ample opportunity to discuss your own data-analytical problems in order to see how you can make use of multi-way analysis.