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WOB
2007
13 years 10 months ago
Gene Set Enrichment Analysis Using Non-parametric Scores
Abstract. Gene Set Enrichment Analysis (GSEA) is a well-known technique used for studying groups of functionally related genes and their correlation with phenotype. This method cre...
Ariel E. Bayá, Mónica G. Larese, Pab...
PE
2002
Springer
176views Optimization» more  PE 2002»
13 years 8 months ago
Effective bandwidth estimation and testing for Markov sources
This work addresses the resource sharing problem in broadband communication networks that can guarantee some quality of service (QoS), and develops some results about data source ...
Juan Pechiar, Gonzalo Perera, María Simon
ECCV
2004
Springer
14 years 2 months ago
Statistical Learning of Evaluation Function for ASM/AAM Image Alignment
Alignment between the input and target objects has great impact on the performance of image analysis and recognition system, such as those for medical image and face recognition. A...
Xiangsheng Huang, Stan Z. Li, Yangsheng Wang
BMCBI
2008
110views more  BMCBI 2008»
13 years 9 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
2006
213views more  BMCBI 2006»
13 years 9 months ago
CoXpress: differential co-expression in gene expression data
Background: Traditional methods of analysing gene expression data often include a statistical test to find differentially expressed genes, or use of a clustering algorithm to find...
Michael Watson