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BIBE
2007
IEEE
153views Bioinformatics» more  BIBE 2007»
13 years 6 months ago
Combined expression data with missing values and gene interaction network analysis: a Markovian integrated approach
—DNA microarray technologies provide means for monitoring in the order of tens of thousands of gene expression levels quantitatively and simultaneously. However data generated in...
Juliette Blanchet, Matthieu Vignes
GPB
2010
231views Solid Modeling» more  GPB 2010»
13 years 2 months ago
Mining Gene Expression Profiles: An Integrated Implementation of Kernel Principal Component Analysis and Singular Value Decompos
The detection of genes that show similar profiles under different experimental conditions is often an initial step in inferring the biological significance of such genes. Visualiz...
Ferran Reverter, Esteban Vegas, Pedro Sánch...
BICOB
2010
Springer
13 years 5 months ago
Integrative Biomarker Discovery for Breast Cancer Metastasis from Gene Expression and Protein Interaction Data Using Error-toler
Biomarker discovery for complex diseases is a challenging problem. Most of the existing approaches identify individual genes as disease markers, thereby missing the interactions a...
Rohit Gupta, Smita Agrawal, Navneet Rao, Ze Tian, ...
AINA
2008
IEEE
13 years 11 months ago
Missing Value Estimation for Time Series Microarray Data Using Linear Dynamical Systems Modeling
The analysis of gene expression time series obtained from microarray experiments can be effectively exploited to understand a wide range of biological phenomena from the homeostat...
Connie Phong, Raul Singh
BMCBI
2008
145views more  BMCBI 2008»
13 years 5 months ago
Mapping gene expression quantitative trait loci by singular value decomposition and independent component analysis
Background: The combination of gene expression profiling with linkage analysis has become a powerful paradigm for mapping gene expression quantitative trait loci (eQTL). To date, ...
Shameek Biswas, John D. Storey, Joshua M. Akey