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» Bayesian Networks Learning for Gene Expression Datasets
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BMCBI
2010
129views more  BMCBI 2010»
14 years 9 months ago
A temporal precedence based clustering method for gene expression microarray data
Background: Time-course microarray experiments can produce useful data which can help in understanding the underlying dynamics of the system. Clustering is an important stage in m...
Ritesh Krishna, Chang-Tsun Li, Vicky Buchanan-Woll...
ICFCA
2007
Springer
15 years 1 months ago
A New and Useful Syntactic Restriction on Rule Semantics for Tabular Datasets
Different rule semantics have been successively defined in many contexts such as implications in artificial intelligence, functional dependencies in databases or association rules...
Marie Agier, Jean-Marc Petit
96
Voted
BMCBI
2007
143views more  BMCBI 2007»
14 years 9 months ago
Gene selection for classification of microarray data based on the Bayes error
Background: With DNA microarray data, selecting a compact subset of discriminative genes from thousands of genes is a critical step for accurate classification of phenotypes for, ...
Ji-Gang Zhang, Hong-Wen Deng
BMCBI
2007
143views more  BMCBI 2007»
14 years 9 months ago
Factor analysis for gene regulatory networks and transcription factor activity profiles
Background: Most existing algorithms for the inference of the structure of gene regulatory networks from gene expression data assume that the activity levels of transcription fact...
Iosifina Pournara, Lorenz Wernisch
111
Voted
BMCBI
2007
207views more  BMCBI 2007»
14 years 9 months ago
Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clus
Background: The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell...
Nikhil R. Pal, Kripamoy Aguan, Animesh Sharma, Shu...