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» Smoothing Gene Expression Using Biological Networks
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ECCB
2003
IEEE
14 years 23 days ago
Gene networks inference using dynamic Bayesian networks
This article deals with the identification of gene regulatory networks from experimental data using a statistical machine learning approach. A stochastic model of gene interactio...
Bruno-Edouard Perrin, Liva Ralaivola, Aurél...
BMCBI
2008
163views more  BMCBI 2008»
13 years 7 months ago
The Annotation, Mapping, Expression and Network (AMEN) suite of tools for molecular systems biology
Background: High-throughput genome biological experiments yield large and multifaceted datasets that require flexible and user-friendly analysis tools to facilitate their interpre...
Frédéric Chalmel, Michael Primig
CSDA
2006
81views more  CSDA 2006»
13 years 7 months ago
Flexible temporal expression profile modelling using the Gaussian process
Time course gene expression experiments have proved valuable in a variety of biological studies [e.g., Chuang, Y., Chen, Y., Gadisetti, V., et al., 2002. Gene expression after tre...
Ming Yuan
IJCNN
2006
IEEE
14 years 1 months ago
Reconstruction of Gene Regulatory Networks from Temporal Microarray Data Using Pattern Recognition Techniques
- Gene regulatory networks allow us to study and understand genes’ roles in biological processes. Among others, regulatory networks help to identify pathway initiator genes and t...
Azhar Salim, Faramarz Valafar
BMCBI
2010
129views more  BMCBI 2010»
13 years 7 months ago
A temporal precedence based clustering method for gene expression microarray data
Background: Time-course microarray experiments can produce useful data which can help in understanding the underlying dynamics of the system. Clustering is an important stage in m...
Ritesh Krishna, Chang-Tsun Li, Vicky Buchanan-Woll...