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» Combined Gene Selection Methods for Microarray Data Analysis
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BMCBI
2007
139views more  BMCBI 2007»
14 years 11 months ago
Significance analysis of microarray transcript levels in time series experiments
Background: Microarray time series studies are essential to understand the dynamics of molecular events. In order to limit the analysis to those genes that change expression over ...
Barbara Di Camillo, Gianna Toffolo, Sreekumaran K....
BMCBI
2010
151views more  BMCBI 2010»
14 years 11 months ago
TF-finder: A software package for identifying transcription factors involved in biological processes using microarray data and e
Background: Identification of transcription factors (TFs) involved in a biological process is the first step towards a better understanding of the underlying regulatory mechanisms...
Xiaoqi Cui, Tong Wang, Huann-Sheng Chen, Victor Bu...
ISMB
2000
15 years 1 months ago
Analysis of Gene Expression Microarrays for Phenotype Classification
Several microarray technologies that monitor the level of expression of a large number of genes have recently emerged. Given DNA-microarray data for a set of cells characterized b...
Andrea Califano, Gustavo Stolovitzky, Yuhai Tu
AUSAI
2007
Springer
15 years 3 months ago
Building Classification Models from Microarray Data with Tree-Based Classification Algorithms
Building classification models plays an important role in DNA mircroarray data analyses. An essential feature of DNA microarray data sets is that the number of input variables (gen...
Peter J. Tan, David L. Dowe, Trevor I. Dix
BMCBI
2010
151views more  BMCBI 2010»
14 years 11 months ago
BABAR: an R package to simplify the normalisation of common reference design microarray-based transcriptomic datasets
Background: The development of DNA microarrays has facilitated the generation of hundreds of thousands of transcriptomic datasets. The use of a common reference microarray design ...
Mark J. Alston, John Seers, Jay C. D. Hinton, Sach...