CUED Publications database

Geometric optimization methods for independent component analysis applied on gene expression data

Journée, M and Teschendorff, AE and Absil, P-A and Sepulchre, R (2007) Geometric optimization methods for independent component analysis applied on gene expression data. In: UNSPECIFIED IV1413-IV1416..

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Abstract

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. © 2007 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Uncontrolled Keywords: Gene expression data Independent Component Analysis (ICA) Optimization on matrix manifolds RADICAL algorithm Steepest-descent on the orthogonal group
Subjects: UNSPECIFIED
Divisions: Div F > Control
Depositing User: Cron Job
Date Deposited: 07 Mar 2014 11:46
Last Modified: 08 Dec 2014 02:23
DOI: 10.1109/ICASSP.2007.367344