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BMCBI
2010
153views more  BMCBI 2010»
14 years 10 months ago
GOAL: A software tool for assessing biological significance of genes groups
Background: Modern high throughput experimental techniques such as DNA microarrays often result in large lists of genes. Computational biology tools such as clustering are then us...
Alain B. Tchagang, Alexander Gawronski, Hugo B&eac...
BIOINFORMATICS
2007
195views more  BIOINFORMATICS 2007»
14 years 10 months ago
Context-dependent clustering for dynamic cellular state modeling of microarray gene expression
Motivation: High-throughput expression profiling allows researchers to study gene activities globally. Genes with similar expression profiles are likely to encode proteins that ma...
Shinsheng Yuan, Ker-Chau Li
BMCBI
2007
239views more  BMCBI 2007»
14 years 10 months ago
Pre-processing Agilent microarray data
Background: Pre-processing methods for two-sample long oligonucleotide arrays, specifically the Agilent technology, have not been extensively studied. The goal of this study is to...
Marianna Zahurak, Giovanni Parmigiani, Wayne Yu, R...
BMCBI
2007
182views more  BMCBI 2007»
14 years 10 months ago
Additive risk survival model with microarray data
Background: Microarray techniques survey gene expressions on a global scale. Extensive biomedical studies have been designed to discover subsets of genes that are associated with ...
Shuangge Ma, Jian Huang
BMCBI
2008
171views more  BMCBI 2008»
14 years 10 months ago
A general approach to simultaneous model fitting and variable elimination in response models for biological data with many more
Background: With the advent of high throughput biotechnology data acquisition platforms such as micro arrays, SNP chips and mass spectrometers, data sets with many more variables ...
Harri T. Kiiveri