Comparison of NMLE with other ICA approaches

2011-12-30T14:12:17Z (GMT) by Su-In Lee Serafim Batzoglou
<p><b>Copyright information:</b></p><p>Taken from "Application of independent component analysis to microarrays"</p><p>Genome Biology 2003;4(11):R76-R76.</p><p>Published online 24 Oct 2003</p><p>PMCID:PMC329130.</p><p>Copyright © 2003 Lee and Batzoglou; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL.</p> Comparison of the NMLE ICA algorithm with three other ICA approaches on two yeast cell cycle data (dataset 1 and 2), yeast stress data (dataset 3), and data (dataset 4). Eight different ICA algorithms and variations (Table ) were compared. The full comparison is shown in the web supplement. Overall, NMLE, ExtIM and FPsymth performed similarly except in the dataset 2. NICApoly performed comparably with NICAgauss. Both nonlinear approaches were better than NMLE in the two smaller datasets, but performed relatively poorly in the two larger datasets.



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