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» Combined Gene Selection Methods for Microarray Data Analysis
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BMCBI
2007
112views more  BMCBI 2007»
14 years 11 months ago
Inferring biological functions and associated transcriptional regulators using gene set expression coherence analysis
Background: Gene clustering has been widely used to group genes with similar expression pattern in microarray data analysis. Subsequent enrichment analysis using predefined gene s...
Tae-Min Kim, Yeun-Jun Chung, Mun-Gan Rhyu, Myeong ...
99
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BMCBI
2007
185views more  BMCBI 2007»
14 years 12 months ago
GEDI: a user-friendly toolbox for analysis of large-scale gene expression data
Background: Several mathematical and statistical methods have been proposed in the last few years to analyze microarray data. Most of those methods involve complicated formulas, a...
André Fujita, João Ricardo Sato, Car...
AIME
2007
Springer
15 years 6 months ago
Interpreting Gene Expression Data by Searching for Enriched Gene Sets
This paper presents a novel method integrating gene-gene interaction information and Gene Ontology for the construction of new gene sets that are potentially enriched. Enrichment o...
Igor Trajkovski, Nada Lavrac
CSB
2005
IEEE
205views Bioinformatics» more  CSB 2005»
15 years 5 months ago
Fractal Clustering for Microarray Data Analysis
DNA microarray experiments generate a substantial amount of information about global gene expression. Gene expression profiles can be represented as points in multi-dimensional sp...
Lu-Yong Wang, Ammaiappan Balasubramanian, Amit Cha...
BMCBI
2006
154views more  BMCBI 2006»
14 years 11 months ago
Analysis with respect to instrumental variables for the exploration of microarray data structures
Background: Evaluating the importance of the different sources of variations is essential in microarray data experiments. Complex experimental designs generally include various fa...
Florent Baty, Michaël Facompré, Jan Wi...