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» Inferring gene regression networks with model trees
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BMCBI
2007
144views more  BMCBI 2007»
13 years 8 months ago
Accelerated search for biomolecular network models to interpret high-throughput experimental data
Background: The functions of human cells are carried out by biomolecular networks, which include proteins, genes, and regulatory sites within DNA that encode and control protein e...
Suman Datta, Bahrad A. Sokhansanj
BMCBI
2006
128views more  BMCBI 2006»
13 years 8 months ago
An interactive tool for visualization of relationships between gene expression profiles
Background: Application of phenetic methods to gene expression analysis proved to be a successful approach. Visualizing the results in a 3-dimentional space may further enhance th...
Peter Ruzanov, Steven J. M. Jones
BMCBI
2008
174views more  BMCBI 2008»
13 years 8 months ago
Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset
Background: Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When only static data are available, gene interact...
Cédric Auliac, Vincent Frouin, Xavier Gidro...
BMCBI
2010
109views more  BMCBI 2010»
13 years 8 months ago
Application of machine learning methods to histone methylation ChIP-Seq data reveals H4R3me2 globally represses gene expression
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...
ECAI
2010
Springer
13 years 6 months ago
Continuous Conditional Random Fields for Regression in Remote Sensing
Conditional random fields (CRF) are widely used for predicting output variables that have some internal structure. Most of the CRF research has been done on structured classificati...
Vladan Radosavljevic, Slobodan Vucetic, Zoran Obra...