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SAC
2006
ACM
14 years 1 months ago
Two-phase clustering strategy for gene expression data sets
In the context of genome research, the method of gene expression analysis has been used for several years. Related microarray experiments are conducted all over the world, and con...
Dirk Habich, Thomas Wächter, Wolfgang Lehner,...
BIBE
2005
IEEE
14 years 1 months ago
Selecting Informative Genes from Microarray Dataset by Incorporating Gene Ontology
Selecting informative genes from microarray experiments is one of the most important data analysis steps for deciphering biological information imbedded in such experiments. Howev...
Xian Xu, Aidong Zhang
AI
2010
Springer
13 years 2 months ago
Annotation Concept Synthesis and Enrichment Analysis
Annotation Enrichment Analysis (AEA) is a widely used analytical approach to process data generated by high-throughput genomic and proteomic experiments such as gene expression mic...
Mikhail Jiline, Stan Matwin, Marcel Turcotte
BIBE
2006
IEEE
139views Bioinformatics» more  BIBE 2006»
14 years 1 months ago
A Computational Inference Framework for analyzing Gene Regulation Pathway using Microarray Data
Microarray experiments produce gene expression data at such a high speed and volume that it is imperative to use highly specialized computational tools for their analyses. One grou...
Dong-Guk Shin, John Bluis, Yoo Ah Kim, Winfried Kr...
BMCBI
2006
147views more  BMCBI 2006»
13 years 8 months ago
Grouping Gene Ontology terms to improve the assessment of gene set enrichment in microarray data
Background: Gene Ontology (GO) terms are often used to assess the results of microarray experiments. The most common way to do this is to perform Fisher's exact tests to find...
Alex Lewin, Ian C. Grieve