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BMCBI
2004
150views more  BMCBI 2004»
13 years 7 months ago
Graph-based iterative Group Analysis enhances microarray interpretation
Background: One of the most time-consuming tasks after performing a gene expression experiment is the biological interpretation of the results by identifying physiologically impor...
Rainer Breitling, Anna Amtmann, Pawel Herzyk
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
2010
115views more  BMCBI 2010»
13 years 7 months ago
Importance of replication in analyzing time-series gene expression data: Corticosteroid dynamics and circadian patterns in rat l
Background: Microarray technology is a powerful and widely accepted experimental technique in molecular biology that allows studying genome wide transcriptional responses. However...
Tung T. Nguyen, Richard R. Almon, Debra C. DuBois,...
BMCBI
2006
158views more  BMCBI 2006»
13 years 7 months ago
Parallelization of multicategory support vector machines (PMC-SVM) for classifying microarray data
Background: Multicategory Support Vector Machines (MC-SVM) are powerful classification systems with excellent performance in a variety of data classification problems. Since the p...
Chaoyang Zhang, Peng Li, Arun Rajendran, Youping D...
BMCBI
2006
82views more  BMCBI 2006»
13 years 7 months ago
Transcriptomic response to differentiation induction
Background: Microarrays used for gene expression studies yield large amounts of data. The processing of such data typically leads to lists of differentially-regulated genes. A com...
G. W. Patton, Robert M. Stephens, I. A. Sidorov, X...