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BMCBI
2007
134views more  BMCBI 2007»
14 years 9 months ago
A framework for significance analysis of gene expression data using dimension reduction methods
Background: The most popular methods for significance analysis on microarray data are well suited to find genes differentially expressed across predefined categories. However, ide...
Lars Halvor Gidskehaug, Endre Anderssen, Arnar Fla...
BMCBI
2008
114views more  BMCBI 2008»
14 years 9 months ago
TiGER: A database for tissue-specific gene expression and regulation
Background: Understanding how genes are expressed and regulated in different tissues is a fundamental and challenging question. However, most of currently available biological dat...
Xiong Liu, Xueping Yu, Donald J. Zack, Heng Zhu, J...
82
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DMIN
2006
151views Data Mining» more  DMIN 2006»
14 years 11 months ago
Rough Set Theory: Approach for Similarity Measure in Cluster Analysis
- Clustering of data is an important data mining application. One of the problems with traditional partitioning clustering methods is that they partition the data into hard bound n...
Shuchita Upadhyaya, Alka Arora, Rajni Jain
IEEEMM
2007
146views more  IEEEMM 2007»
14 years 9 months ago
Learning Microarray Gene Expression Data by Hybrid Discriminant Analysis
— Microarray technology offers a high throughput means to study expression networks and gene regulatory networks in cells. The intrinsic nature of high dimensionality and small s...
Yijuan Lu, Qi Tian, Maribel Sanchez, Jennifer L. N...
RECOMB
2002
Springer
15 years 10 months ago
Discovering local structure in gene expression data: the order-preserving submatrix problem
This paper concerns the discovery of patterns in gene expression matrices, in which each element gives the expression level of a given gene in a given experiment. Most existing me...
Amir Ben-Dor, Benny Chor, Richard M. Karp, Zohar Y...