2009 • In Verleysen, Michel (Ed.) ESANN'2009 proceedings, European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning.
[en] We propose a “time-biased” and a “space-biased” method for
spatiotemporal independent component analysis (ICA). The methods rely
on computing an orthogonal approximate joint diagonalizer of a collection
of covariance-like matrices. In the time-biased version, the time signatures
of the ICA modes are imposed to be white, whereas the space-biased version
imposes the same condition on the space signatures. We apply the
two methods to the analysis of gene expression data, where the genes play
the role of the space and the cell samples stand for the time. This study
is a step towards addressing a question first raised by Liebermeister, on
whether ICA methods for gene expression analysis should impose independence
across genes or across cell samples. Our preliminary experiment
indicates that both approaches have value, and that exploring the continuum
between these two extremes can provide useful information about the
interactions between genes and their impact on the phenotype.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Wolfram Liebermeister. Linear modes of gene expression determined by independent component analysis. Bioinformatics, 18 (1): 51-60, 2002.
Andrew E. Teschendorff, Michel Journée, Pierre A. Absil, Rodolphe Sepulchre, and Carlos Caldas. Elucidating the altered transcriptional programs in breast cancer using independent component analysis. PLoS Comput. Biol., 3 (8): 1539-1554, 2007. doi:10.1371/journal.pcbi.0030161.
J. V. Stone, J. Porrill, N. R. Porter, and I. D. Wilkinson. Spatiotemporal independent component analysis of event-related fmri data using skewed probability density functions. NeuroImage, 15: 407-421, 2002.
Fabian J. Theis, Peter Gruber, Ingo R. Keck, Anke Meyer-Bäse, and Elmar W. Lang. Spatiotemporal blind source separation using double-sided approximate joint diagonalization. In Proc. EUSIPCO, Antalya, Turkey, 2005. Available from http://fabian.theis.name/.
P. -A. Absil, R. Mahony, and R. Sepulchre. Optimization Algorithms on Matrix Manifolds. Princeton University Press, Princeton, NJ, 2008.
J. F. Cardoso and A. Souloumiac. Blind beamforming for non-gaussian signals. IEE Proceedings - F, 140 (6): 362-370, 1993.
Fabian J. Theis, Thomas P. Cason, and P. -A. Absil. Soft dimension reduction for ICA by joint diagonalization on the Stiefel manifold. Technical Report UCL-INMA-2008. 155, Department of Mathematical Engineering, Université catholique de Louvain, 2008. Accepted for publication in the proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation (ICA2009).
Yixin Wang, Jan GM Klij, Yi Zhang, and Anieta M Sieuwerts. Geneexpression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet, 365: 671-679, 2005.
Similar publications
Sorry the service is unavailable at the moment. Please try again later.
This website uses cookies to improve user experience. Read more
Save & Close
Accept all
Decline all
Show detailsHide details
Cookie declaration
About cookies
Strictly necessary
Performance
Strictly necessary cookies allow core website functionality such as user login and account management. The website cannot be used properly without strictly necessary cookies.
This cookie is used by Cookie-Script.com service to remember visitor cookie consent preferences. It is necessary for Cookie-Script.com cookie banner to work properly.
Performance cookies are used to see how visitors use the website, eg. analytics cookies. Those cookies cannot be used to directly identify a certain visitor.
Used to store the attribution information, the referrer initially used to visit the website
Cookies are small text files that are placed on your computer by websites that you visit. Websites use cookies to help users navigate efficiently and perform certain functions. Cookies that are required for the website to operate properly are allowed to be set without your permission. All other cookies need to be approved before they can be set in the browser.
You can change your consent to cookie usage at any time on our Privacy Policy page.