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» Gene Expression Data Management: A Case Study
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BMCBI
2006
91views more  BMCBI 2006»
13 years 6 months ago
Empirical study of supervised gene screening
Background: Microarray studies provide a way of linking variations of phenotypes with their genetic causations. Constructing predictive models using high dimensional microarray me...
Shuangge Ma
JIB
2007
88views more  JIB 2007»
13 years 6 months ago
Achieving k-anonymity in DataMarts used for gene expressions exploitation
Gene expression profiling is a sophisticated method to discover differences in activation patterns of genes between different patient collectives. By reasonably defining patient...
Konrad Stark, Johann Eder, Kurt Zatloukal
IJON
2008
128views more  IJON 2008»
13 years 6 months ago
Independent arrays or independent time courses for gene expression time series data analysis
In this paper we apply three different independent component analysis (ICA) methods, including spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA), to gene exp...
Sookjeong Kim, Jong Kyoung Kim, Seungjin Choi
BMCBI
2011
12 years 10 months ago
Evaluating methods for ranking differentially expressed genes applied to MicroArray Quality Control data
Background: Statistical methods for ranking differentially expressed genes (DEGs) from gene expression data should be evaluated with regard to high sensitivity, specificity, and r...
Koji Kadota, Kentaro Shimizu
BMCBI
2004
124views more  BMCBI 2004»
13 years 6 months ago
Tests for finding complex patterns of differential expression in cancers: towards individualized medicine
Background: Microarray studies in cancer compare expression levels between two or more sample groups on thousands of genes. Data analysis follows a population-level approach (e.g....
James Lyons-Weiler, Satish Patel, Michael J. Becic...