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» Extracting active pathways from gene expression data
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JIB
2007
88views more  JIB 2007»
13 years 7 months ago
Achieving k-anonymity in DataMarts used for gene expressions exploitation
Gene expression profiling is a sophisticated method to discover differences in activation patterns of genes between different patient collectives. By reasonably defining patient...
Konrad Stark, Johann Eder, Kurt Zatloukal
CANDC
2005
ACM
13 years 7 months ago
Gene selection from microarray data for cancer classification - a machine learning approach
A DNA microarray can track the expression levels of thousands of genes simultaneously. Previous research has demonstrated that this technology can be useful in the classification ...
Yu Wang 0008, Igor V. Tetko, Mark A. Hall, Eibe Fr...
BMCBI
2006
123views more  BMCBI 2006»
13 years 7 months ago
Characterizing disease states from topological properties of transcriptional regulatory networks
Background: High throughput gene expression experiments yield large amounts of data that can augment our understanding of disease processes, in addition to classifying samples. He...
David Tuck, Harriet Kluger, Yuval Kluger
BIBE
2008
IEEE
111views Bioinformatics» more  BIBE 2008»
13 years 9 months ago
Structure learning for biomolecular pathways containing cycles
Bayesian network structure learning is a useful tool for elucidation of regulatory structures of biomolecular pathways. The approach however is limited by its acyclicity constraint...
S. Itani, Karen Sachs, Garry P. Nolan, M. A. Dahle...
BMCBI
2008
111views more  BMCBI 2008»
13 years 7 months ago
Information-based methods for predicting gene function from systematic gene knock-downs
Background: The rapid annotation of genes on a genome-wide scale is now possible for several organisms using high-throughput RNA interference assays to knock down the expression o...
Matthew T. Weirauch, Christopher K. Wong, Alexandr...