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» Smoothing Gene Expression Using Biological Networks
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DIS
2004
Springer
14 years 27 days ago
A Methodology for Biologically Relevant Pattern Discovery from Gene Expression Data
Abstract. One of the most exciting scientific challenges in functional genomics concerns the discovery of biologically relevant patterns from gene expression data. For instance, i...
Ruggero G. Pensa, Jérémy Besson, Jea...
BMCBI
2010
153views more  BMCBI 2010»
13 years 6 months ago
DiffCoEx: a simple and sensitive method to find differentially coexpressed gene modules
Background: Large microarray datasets have enabled gene regulation to be studied through coexpression analysis. While numerous methods have been developed for identifying differen...
Bruno M. Tesson, Rainer Breitling, Ritsert C. Jans...
CBMS
2006
IEEE
13 years 9 months ago
Incorporating Gene Ontology in Clustering Gene Expression Data
In this paper we consider a general framework for clustering expression data that permits integration of various biological data sources through combination of corresponding dissi...
Rafal Kustra, Adam Zagdanski
ALIFE
2008
13 years 7 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...
BMCBI
2008
166views more  BMCBI 2008»
13 years 7 months ago
Biclustering via optimal re-ordering of data matrices in systems biology: rigorous methods and comparative studies
Background: The analysis of large-scale data sets via clustering techniques is utilized in a number of applications. Biclustering in particular has emerged as an important problem...
Peter A. DiMaggio Jr., Scott R. McAllister, Christ...