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» Smoothing Gene Expression Using Biological Networks
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ISDA
2008
IEEE
14 years 3 months ago
Combining Clustering and Bayesian Network for Gene Network Inference
Gene network reconstruction is a multidisciplinary research area involving data mining, machine learning, statistics, ontologies and others. Reconstructed gene network allows us t...
Suhaila Zainudin, Safaai Deris
CISIS
2010
IEEE
13 years 6 months ago
Modeling of Stress-induced Regulatory Cascades Involving Transcription Factor Dimers
Regulatory cascades consisting of stress-induced gene modules and their transcriptional regulators were recently identified and quantitatively modeled using Artificial Neural Netwo...
Maria Manioudaki, Panayiota Poirazi
RECOMB
2006
Springer
14 years 9 months ago
Detecting MicroRNA Targets by Linking Sequence, MicroRNA and Gene Expression Data
MicroRNAs (miRNAs) have recently been discovered as an important class of non-coding RNA genes that play a major role in regulating gene expression, providing a means to control th...
Jim C. Huang, Quaid Morris, Brendan J. Frey
BIBE
2004
IEEE
107views Bioinformatics» more  BIBE 2004»
14 years 18 days ago
Enhanced pClustering and Its Applications to Gene Expression Data
Clustering has been one of the most popular methods to discover useful biological insights from DNA microarray. An interesting paradigm is simultaneous clustering of both genes an...
Sungroh Yoon, Christine Nardini, Luca Benini, Giov...
IMSCCS
2006
IEEE
14 years 2 months ago
Clustering of Gene Expression Data: Performance and Similarity Analysis
Background: DNA Microarray technology is an innovative methodology in experimental molecular biology, which has produced huge amounts of valuable data in the profile of gene expre...
Longde Yin, Chun-Hsi Huang