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» Unfolding of Microarray Data
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ACSC
2005
IEEE
14 years 1 months ago
Integer Programming Models and Algorithms for Molecular Classification of Cancer from Microarray Data
Novel, high-throughput technologies are challenging the core of algorithmic methods available in Computer Science. Microarray technologies give Life Sciences researchers the oppor...
Regina Berretta, Alexandre Mendes, Pablo Moscato
BMCBI
2004
75views more  BMCBI 2004»
13 years 8 months ago
Joint analysis of two microarray gene-expression data sets to select lung adenocarcinoma marker genes
Background: Due to the high cost and low reproducibility of many microarray experiments, it is not surprising to find a limited number of patient samples in each study, and very f...
Hongying Jiang, Youping Deng, Huann-Sheng Chen, Li...
BMCBI
2006
119views more  BMCBI 2006»
13 years 8 months ago
Evaluation of microarray data normalization procedures using spike-in experiments
Background: Recently, a large number of methods for the analysis of microarray data have been proposed but there are few comparisons of their relative performances. By using so-ca...
Patrik Rydén, Henrik Andersson, Mattias Lan...
BMCBI
2008
121views more  BMCBI 2008»
13 years 8 months ago
Microarray data mining using landmark gene-guided clustering
Background: Clustering is a popular data exploration technique widely used in microarray data analysis. Most conventional clustering algorithms, however, generate only one set of ...
Pankaj Chopra, Jaewoo Kang, Jiong Yang, HyungJun C...
RECOMB
2001
Springer
14 years 8 months ago
Analysis techniques for microarray time-series data
We address possible limitations of publicly available data sets of yeast gene expression. We study the predictability of known regulators via time-series analysis, and show that l...
Vladimir Filkov, Steven Skiena, Jizu Zhi