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BMCBI
2010
152views more  BMCBI 2010»
13 years 4 months ago
Comparative study of discretization methods of microarray data for inferring transcriptional regulatory networks
Background: Microarray data discretization is a basic preprocess for many algorithms of gene regulatory network inference. Some common discretization methods in informatics are us...
Yong Li, Lili Liu, Xi Bai, Hua Cai, Wei Ji, Dianji...
BMCBI
2007
130views more  BMCBI 2007»
13 years 4 months ago
A model-based optimization framework for the inference of regulatory interactions using time-course DNA microarray expression da
Background: Proteins are the primary regulatory agents of transcription even though mRNA expression data alone, from systems like DNA microarrays, are widely used. In addition, th...
Reuben Thomas, Carlos J. Paredes, Sanjay Mehrotra,...
BMCBI
2004
146views more  BMCBI 2004»
13 years 4 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
178views more  BMCBI 2005»
13 years 4 months ago
A quantization method based on threshold optimization for microarray short time series
Background: Reconstructing regulatory networks from gene expression profiles is a challenging problem of functional genomics. In microarray studies the number of samples is often ...
Barbara Di Camillo, Fatima Sanchez-Cabo, Gianna To...
BMCBI
2008
166views more  BMCBI 2008»
13 years 4 months ago
Learning transcriptional regulatory networks from high throughput gene expression data using continuous three-way mutual informa
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
Weijun Luo, Kurt D. Hankenson, Peter J. Woolf