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BMCBI
2008
99views more  BMCBI 2008»
13 years 7 months ago
Ranking analysis of F-statistics for microarray data
Background: Microarray technology provides an efficient means for globally exploring physiological processes governed by the coordinated expression of multiple genes. However, ide...
Yuan-De Tan, Myriam Fornage, Hongyan Xu
BMCBI
2006
183views more  BMCBI 2006»
13 years 7 months ago
Mining gene expression data by interpreting principal components
Background: There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many insta...
Joseph C. Roden, Brandon W. King, Diane Trout, Ali...
TCSB
2008
13 years 7 months ago
Clustering Time-Series Gene Expression Data with Unequal Time Intervals
Clustering gene expression data given in terms of time-series is a challenging problem that imposes its own particular constraints, namely exchanging two or more time points is not...
Luis Rueda, Ataul Bari, Alioune Ngom
BMCBI
2010
164views more  BMCBI 2010»
13 years 5 months ago
Merged consensus clustering to assess and improve class discovery with microarray data
Background: One of the most commonly performed tasks when analysing high throughput gene expression data is to use clustering methods to classify the data into groups. There are a...
T. Ian Simpson, J. Douglas Armstrong, Andrew P. Ja...
JIB
2007
88views more  JIB 2007»
13 years 7 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