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A Nonparametric Likelihood Ratio Test to Identify Differentially Expressed Genes from Microarray Data

A Nonparametric Likelihood Ratio Test to Identify Differentially Expressed Genes from Microarray... Microarray experiments contribute significantly to the progress in disease treatment by enabling a precise and early diagnosis. One of the major objectives of microarray experiments is to identify differentially expressed genes under various conditions. The statistical methods currently used to analyse microarray data are inadequate, mainly due to the lack of understanding of the distribution of microarray data. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Bioinformatics Springer Journals

A Nonparametric Likelihood Ratio Test to Identify Differentially Expressed Genes from Microarray Data

Applied Bioinformatics , Volume 5 (4) – Aug 22, 2012

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References (31)

Publisher
Springer Journals
Copyright
Copyright © 2006 by Adis Data Information BV
Subject
Pharmacy; Pharmacy
ISSN
1175-5636
DOI
10.2165/00822942-200605040-00009
Publisher site
See Article on Publisher Site

Abstract

Microarray experiments contribute significantly to the progress in disease treatment by enabling a precise and early diagnosis. One of the major objectives of microarray experiments is to identify differentially expressed genes under various conditions. The statistical methods currently used to analyse microarray data are inadequate, mainly due to the lack of understanding of the distribution of microarray data.

Journal

Applied BioinformaticsSpringer Journals

Published: Aug 22, 2012

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