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    » Smoothing Gene Expression Using Biological Networks
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    BMCBI
    2010
    109views more  BMCBI 2010»
    Application of machine learning methods to histone methylation ChIP-Seq data reveals H4R3me2 globally represses gene expression
    13 years 9 months ago
    Application of machine learning methods to histone methylation ChIP-Seq data reveals H4R3me2 globally represses gene expression
    Download  www.biomedcentral.com
    Background: In the last decade, biochemical studies have revealed that epigenetic modifications including histone modifications, histone variants and DNA methylation form a comple...
    Xiaojiang Xu, Stephen Hoang, Marty W. Mayo, Stefan...
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    TCBB
    2010
    136views more  TCBB 2010»
    Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data
    13 years 7 months ago
    Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data
    Download  www.ics.uci.edu
    — The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses ...
    Oliver Rübel, Gunther H. Weber, Min-Yu Huang,...
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    BMCBI
    2010
    160views more  BMCBI 2010»
    Extracting consistent knowledge from highly inconsistent cancer gene data sources
    13 years 9 months ago
    Extracting consistent knowledge from highly inconsistent cancer gene data sources
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    Background: Hundreds of genes that are causally implicated in oncogenesis have been found and collected in various databases. For efficient application of these abundant but diver...
    Xue Gong, Ruihong Wu, Yuannv Zhang, Wenyuan Zhao, ...
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    BMCBI
    2005
    107views more  BMCBI 2005»
    Identifying differential expression in multiple SAGE libraries: an overdispersed log-linear model approach
    13 years 8 months ago
    Identifying differential expression in multiple SAGE libraries: an overdispersed log-linear model approach
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    Background: In testing for differential gene expression involving multiple serial analysis of gene expression (SAGE) libraries, it is critical to account for both between and with...
    Jun Lu, John K. Tomfohr, Thomas B. Kepler
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    DILS
    2005
    Springer
    174views Life Sciences» more  DILS 2005»
    Integrating Heterogeneous Microarray Data Sources Using Correlation Signatures
    14 years 2 months ago
    Integrating Heterogeneous Microarray Data Sources Using Correlation Signatures
    Download  infos.korea.ac.kr
    Abstract. Microarrays are one of the latest breakthroughs in experimental molecular biology. Thousands of different research groups generate tens of thousands of microarray gene e...
    Jaewoo Kang, Jiong Yang, Wanhong Xu, Pankaj Chopra
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