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BMCBI
2007
139views more  BMCBI 2007»
13 years 7 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
2006
211views more  BMCBI 2006»
13 years 7 months ago
Missing value estimation for DNA microarray gene expression data by Support Vector Regression imputation and orthogonal coding s
Background: Gene expression profiling has become a useful biological resource in recent years, and it plays an important role in a broad range of areas in biology. The raw gene ex...
Xian Wang, Ao Li, Zhaohui Jiang, Huanqing Feng
BMCBI
2007
169views more  BMCBI 2007»
13 years 7 months ago
Transcriptional regulatory network refinement and quantification through kinetic modeling, gene expression microarray data and i
Background: Gene expression microarray and other multiplex data hold promise for addressing the challenges of cellular complexity, refined diagnoses and the discovery of well-targ...
Abdallah Sayyed-Ahmad, Kagan Tuncay, Peter J. Orto...
ISBRA
2009
Springer
14 years 2 months ago
Practical Quality Assessment of Microarray Data by Simulation of Differential Gene Expression
There are many methods for assessing the quality of microarray data, but little guidance regarding what to do when defective data is identified. Depending on the scientific questio...
Brian E. Howard, Beate Sick, Steffen Heber
BMCBI
2008
104views more  BMCBI 2008»
13 years 7 months ago
Missing value imputation improves clustering and interpretation of gene expression microarray data
Background: Missing values frequently pose problems in gene expression microarray experiments as they can hinder downstream analysis of the datasets. While several missing value i...
Johannes Tuikkala, Laura Elo, Olli Nevalainen, Ter...