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Unsupervised reduction of the dimensionality followed by supervised learning with a perceptron improves the classification of conditions in DNA microarray gene expression data.

, , , and . NNSP, page 77-86. IEEE, (2002)

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Unsupervised reduction of the dimensionality followed by supervised learning with a perceptron improves the classification of conditions in DNA microarray gene expression data., , , and . NNSP, page 77-86. IEEE, (2002)eALPS: Estimating Abundance Levels in Pooled Sequencing Using Available Genotyping Data., , , , , , and . RECOMB, volume 7821 of Lecture Notes in Computer Science, page 32-44. Springer, (2013)Improved Class Prediction in DNA Microarray Gene Expression Data by Unsupervised Reduction of the Dimensionality followed by Supervised Learning with a Perceptron., , , and . J. VLSI Signal Process., 35 (3): 245-253 (2003)Finding SNPs with Putative Phenotypic Effect at Transcriptional Level., , , , and . Spanish Bioinformatics Conference, page 157-160. Technical University of Catalonia, Barcelona, (2004)New challenges in gene expression data analysis and the extended GEPAS., , , , , , , and . Nucleic Acids Res., 32 (Web-Server-Issue): 485-491 (2004)PRRC2A and BCL2L11 gene variants influence risk of non-Hodgkin lymphoma: results from the InterLymph consortium., , , , , , , , , and 33 other author(s). Blood, 120 (23): 4645--4648 (Nov 29, 2012)Genome-wide association study of follicular lymphoma identifies a risk locus at 6p21.32., , , , , , , , , and 61 other author(s). Nature genetics, 42 (8): 661--664 (August 2010)A comprehensive study of polymorphisms in the ABCB1, ABCC2, ABCG2, NR1I2 genes and lymphoma risk., , , , , , , , , and 13 other author(s). International journal of cancer. Journal international du cancer, 131 (4): 803--812 (Aug 15, 2012)