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DILS
2009
Springer
14 years 2 months ago
Integration of Full-Coverage Probabilistic Functional Networks with Relevance to Specific Biological Processes
Probabilistic functional integrated networks are powerful tools with which to draw inferences from high-throughput data. However, network analyses are generally not tailored to spe...
Katherine James, Anil Wipat, Jennifer Hallinan
CSB
2005
IEEE
205views Bioinformatics» more  CSB 2005»
14 years 1 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...
BMEI
2008
IEEE
13 years 9 months ago
Clustering of High-Dimensional Gene Expression Data with Feature Filtering Methods and Diffusion Maps
The importance of gene expression data in cancer diagnosis and treatment by now has been widely recognized by cancer researchers in recent years. However, one of the major challen...
Rui Xu, Steven Damelin, Boaz Nadler, Donald C. Wun...
BICOB
2009
Springer
13 years 5 months ago
A Biclustering Method to Discover Co-regulated Genes Using Diverse Gene Expression Datasets
We propose a two-step biclustering approach to mine co-regulation patterns of a given reference gene to discover other genes that function in a common biological process. Currently...
Doruk Bozdag, Jeffrey D. Parvin, Ümit V. &Cce...
BMCBI
2006
165views more  BMCBI 2006»
13 years 7 months ago
A stable gene selection in microarray data analysis
Background: Microarray data analysis is notorious for involving a huge number of genes compared to a relatively small number of samples. Gene selection is to detect the most signi...
Kun Yang, Zhipeng Cai, Jianzhong Li, Guohui Lin