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» Smoothing Gene Expression Using Biological Networks
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BMCBI
2007
144views more  BMCBI 2007»
13 years 7 months ago
Spectral estimation in unevenly sampled space of periodically expressed microarray time series data
Background: Periodogram analysis of time-series is widespread in biology. A new challenge for analyzing the microarray time series data is to identify genes that are periodically ...
Alan Wee-Chung Liew, Jun Xian, Shuanhu Wu, David K...
RECOMB
2007
Springer
14 years 7 months ago
Learning Gene Regulatory Networks via Globally Regularized Risk Minimization
Learning the structure of a gene regulatory network from time-series gene expression data is a significant challenge. Most approaches proposed in the literature to date attempt to ...
Yuhong Guo, Dale Schuurmans
BMCBI
2008
160views more  BMCBI 2008»
13 years 7 months ago
Predicting cancer involvement of genes from heterogeneous data
Background: Systematic approaches for identifying proteins involved in different types of cancer are needed. Experimental techniques such as microarrays are being used to characte...
Ramon Aragues, Chris Sander, Baldo Oliva
BMCBI
2010
155views more  BMCBI 2010»
13 years 7 months ago
A bi-ordering approach to linking gene expression with clinical annotations in gastric cancer
Background: In the study of cancer genomics, gene expression microarrays, which measure thousands of genes in a single assay, provide abundant information for the investigation of...
Fan Shi, Christopher Leckie, Geoff MacIntyre, Izha...
BMCBI
2011
13 years 2 months ago
The impact of quantitative optimization of hybridization conditions on gene expression analysis
Background: With the growing availability of entire genome sequences, an increasing number of scientists can exploit oligonucleotide microarrays for genome-scale expression studie...
Peter Sykacek, David P. Kreil, Lisa A. Meadows, Ri...