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BMCBI
2010
208views more  BMCBI 2010»
13 years 7 months ago
Using machine learning to speed up manual image annotation: application to a 3D imaging protocol for measuring single cell gene
Background: Image analysis is an essential component in many biological experiments that study gene expression, cell cycle progression, and protein localization. A protocol for tr...
Zafer Aydin, John I. Murray, Robert H. Waterston, ...
RECOMB
2002
Springer
14 years 7 months ago
From promoter sequence to expression: a probabilistic framework
We present a probabilistic framework that models the process by which transcriptional binding explains the mRNA expression of different genes. Our joint probabilistic model unifie...
Eran Segal, Yoseph Barash, Itamar Simon, Nir Fried...
BMCBI
2004
146views more  BMCBI 2004»
13 years 7 months ago
Defining transcriptional networks through integrative modeling of mRNA expression and transcription factor binding data
Background: Functional genomics studies are yielding information about regulatory processes in the cell at an unprecedented scale. In the yeast S. cerevisiae, DNA microarrays have...
Feng Gao, Barrett C. Foat, Harmen J. Bussemaker
BMCBI
2005
121views more  BMCBI 2005»
13 years 7 months ago
Evaluation of gene importance in microarray data based upon probability of selection
Background: Microarray devices permit a genome-scale evaluation of gene function. This technology has catalyzed biomedical research and development in recent years. As many import...
Li M. Fu, Casey S. Fu-Liu
BMCBI
2004
115views more  BMCBI 2004»
13 years 7 months ago
Quantifying the relationship between co-expression, co-regulation and gene function
Background: It is thought that genes with similar patterns of mRNA expression and genes with similar functions are likely to be regulated via the same mechanisms. It has been diff...
Dominic J. Allocco, Isaac S. Kohane, Atul J. Butte