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» Clustering Gene Expression Series with Prior Knowledge
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BMCBI
2007
152views more  BMCBI 2007»
13 years 7 months ago
Difference-based clustering of short time-course microarray data with replicates
Background: There are some limitations associated with conventional clustering methods for short time-course gene expression data. The current algorithms require prior domain know...
Jihoon Kim, Ju Han Kim
BMCBI
2006
157views more  BMCBI 2006»
13 years 7 months ago
Determination of the minimum number of microarray experiments for discovery of gene expression patterns
Background: One type of DNA microarray experiment is discovery of gene expression patterns for a cell line undergoing a biological process over a series of time points. Two import...
Fang-Xiang Wu, W. J. Zhang, Anthony J. Kusalik
CSB
2003
IEEE
130views Bioinformatics» more  CSB 2003»
14 years 22 days ago
Latent Structure Models for the Analysis of Gene Expression Data
Cluster methods have been successfully applied in gene expression data analysis to address tumor classification. By grouping tissue samples into homogeneous subsets, more systema...
Dong Hua, Dechang Chen, Xiuzhen Cheng, Abdou Youss...
RECOMB
2002
Springer
14 years 7 months ago
A new approach to analyzing gene expression time series data
We present algorithms for time-series gene expression analysis that permit the principled estimation of unobserved timepoints, clustering, and dataset alignment. Each expression p...
Ziv Bar-Joseph, Georg Gerber, David K. Gifford, To...
ICASSP
2008
IEEE
14 years 1 months ago
Probabilistic framework for gene expression clustering validation based on gene ontology and graph theory
Based on the correlation between expression and ontologydriven gene similarity, we incorporate functional annotations into gene expression clustering validation. A probabilistic f...
Yinyin Yuan, Chang-Tsun Li