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» Two-phase clustering strategy for gene expression data sets
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ISDA
2008
IEEE
15 years 3 months ago
Combining Clustering and Bayesian Network for Gene Network Inference
Gene network reconstruction is a multidisciplinary research area involving data mining, machine learning, statistics, ontologies and others. Reconstructed gene network allows us t...
Suhaila Zainudin, Safaai Deris
BMCBI
2005
152views more  BMCBI 2005»
14 years 9 months ago
CoPub Mapper: mining MEDLINE based on search term co-publication
Background: High throughput microarray analyses result in many differentially expressed genes that are potentially responsible for the biological process of interest. In order to ...
Blaise T. F. Alako, Antoine Veldhoven, Sjozef van ...
BMCBI
2008
167views more  BMCBI 2008»
14 years 9 months ago
Expression profiles of switch-like genes accurately classify tissue and infectious disease phenotypes in model-based classificat
Background: Large-scale compilation of gene expression microarray datasets across diverse biological phenotypes provided a means of gathering a priori knowledge in the form of ide...
Michael Gormley, Aydin Tozeren
70
Voted
BIOCOMP
2006
14 years 11 months ago
A Heuristic Approach to Scoring Gene Clustering Algorithms
In the past decades, many clustering algorithms have been proposed for the analysis of gene expression data, but little guidance is available to help choose among them. Given the ...
Longde Yin, Chun-Hsi Huang
NAR
2000
117views more  NAR 2000»
14 years 9 months ago
The TIGR Gene Indices: reconstruction and representation of expressed gene sequences
Expressed sequence tags (ESTs) have provided a first glimpse of the collection of transcribed sequences in a variety of organisms. However, a careful analysis of this sequence dat...
John Quackenbush, Feng Liang, Ingeborg Holt, Geo P...