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BMCBI
2010
172views more  BMCBI 2010»
13 years 5 months ago
Inferring gene regression networks with model trees
Background: Novel strategies are required in order to handle the huge amount of data produced by microarray technologies. To infer gene regulatory networks, the first step is to f...
Isabel A. Nepomuceno-Chamorro, Jesús S. Agu...
BMCBI
2010
160views more  BMCBI 2010»
13 years 5 months ago
Quantitative model for inferring dynamic regulation of the tumour suppressor gene p53
Background: The availability of various "omics" datasets creates a prospect of performing the study of genomewide genetic regulatory networks. However, one of the major ...
Junbai Wang, Tianhai Tian
BMCBI
2007
143views more  BMCBI 2007»
13 years 5 months ago
Factor analysis for gene regulatory networks and transcription factor activity profiles
Background: Most existing algorithms for the inference of the structure of gene regulatory networks from gene expression data assume that the activity levels of transcription fact...
Iosifina Pournara, Lorenz Wernisch
BMCBI
2008
166views more  BMCBI 2008»
13 years 5 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
ALIFE
2008
13 years 5 months ago
Exploring the Operational Characteristics of Inference Algorithms for Transcriptional Networks by Means of Synthetic Data
The development of structure-learning algorithms for gene regulatory networks depends heavily on the availability of synthetic data sets that contain both the original network and ...
Koenraad Van Leemput, Tim Van den Bulcke, Thomas D...