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BMCBI
2004
181views more  BMCBI 2004»
13 years 7 months ago
Iterative class discovery and feature selection using Minimal Spanning Trees
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
Sudhir Varma, Richard Simon
BIOCOMP
2007
13 years 9 months ago
Biomarker Discovery Across Annotated and Unannotated Microarray Datasets Using Semi-Supervised Learning
The growing body of DNA microarray data has the potential to advance our understanding of the molecular basis of disease. However annotating microarray datasets with clinically us...
Cole Harris, Noushin Ghaffari
ICPR
2006
IEEE
14 years 8 months ago
Finding Rule Groups to Classify High Dimensional Gene Expression Datasets
Microarray data provides quantitative information about the transcription profile of cells. To analyze microarray datasets, methodology of machine learning has increasingly attrac...
Jiyuan An, Yi-Ping Phoebe Chen
BMCBI
2008
110views more  BMCBI 2008»
13 years 7 months ago
Testing for treatment effects on gene ontology
In studies that use DNA arrays to assess changes in gene expression, it is preferable to measure the significance of treatment effects on a group of genes from a pathway or functi...
Taewon Lee, Varsha G. Desai, Cruz Velasco, Robert ...
BMCBI
2007
149views more  BMCBI 2007»
13 years 7 months ago
A unified framework for finding differentially expressed genes from microarray experiments
Background: This paper presents a unified framework for finding differentially expressed genes (DEGs) from the microarray data. The proposed framework has three interrelated modul...
Jahangheer S. Shaik, Mohammed Yeasin