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JIPS
2007
134views more  JIPS 2007»
13 years 7 months ago
An Efficient Functional Analysis Method for Micro-array Data Using Gene Ontology
: Microarray data includes tens of thousands of gene expressions simultaneously, so it can be effectively used in identifying the phenotypes of diseases. However, the retrieval of ...
Dong-wan Hong, Jong-keun Lee, Sung-soo Park, Sang-...
BIBM
2009
IEEE
192views Bioinformatics» more  BIBM 2009»
14 years 2 months ago
A Multi-task Feature Selection Filter for Microarray Classification
A major challenge in microarray classification and biomarker discovery is dealing with small-sample high-dimensional data where the number of genes used as features is typically o...
Liang Lan, Slobodan Vucetic
BMCBI
2007
207views more  BMCBI 2007»
13 years 7 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...
BMCBI
2007
171views more  BMCBI 2007»
13 years 7 months ago
Classification of microarray data using gene networks
Background: Microarrays have become extremely useful for analysing genetic phenomena, but establishing a relation between microarray analysis results (typically a list of genes) a...
Franck Rapaport, Andrei Zinovyev, Marie Dutreix, E...
ISMB
2000
13 years 8 months ago
Analysis of Gene Expression Microarrays for Phenotype Classification
Several microarray technologies that monitor the level of expression of a large number of genes have recently emerged. Given DNA-microarray data for a set of cells characterized b...
Andrea Califano, Gustavo Stolovitzky, Yuhai Tu