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Geometric Optimization Methods for Independent Component Analysis Applied on Gene Expression Data

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4 Author(s)
M. Journee ; Dept. of Electrical Engineering and Computer Science, University of Liège, Belgium. ; A. E. Teschendorff ; P. -A. Absil ; R. Sepulchre

DNA microarrays provide a huge amount of data and require therefore dimensionality reduction methods to extract meaningful biological information. Independent component analysis (ICA) was proposed by several authors as an interesting means. Unfortunately, experimental data are usually of poor quality because of noise, outliers and lack of samples. Robustness to these hurdles will thus be a key feature for an ICA algorithm. This paper identifies a robust contrast function and proposes a new ICA algorithm.

Published in:

2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07  (Volume:4 )

Date of Conference:

15-20 April 2007