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» Predicting Peroxisomal Proteins
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ECCB
2003
IEEE
14 years 1 months 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...
DILS
2006
Springer
13 years 11 months ago
Link Discovery in Graphs Derived from Biological Databases
Public biological databases contain vast amounts of rich data that can also be used to create and evaluate new biological hypothesis. We propose a method for link discovery in biol...
Petteri Sevon, Lauri Eronen, Petteri Hintsanen, Ki...
BIRD
2008
Springer
131views Bioinformatics» more  BIRD 2008»
13 years 10 months ago
Identifying Subcellular Locations from Images of Unknown Resolution
Our group has previously used machine learning techniques to develop computational systems to automatically analyse fluorescence microscope images and classify the location of the ...
Luís Pedro Coelho, Robert F. Murphy
RECOMB
2010
Springer
13 years 9 months ago
Subnetwork State Functions Define Dysregulated Subnetworks in Cancer
Abstract. Emerging research demonstrates the potential of proteinprotein interaction (PPI) networks in uncovering the mechanistic bases of cancers, through identification of intera...
Salim A. Chowdhury, Rod K. Nibbe, Mark R. Chance, ...
SDM
2008
SIAM
139views Data Mining» more  SDM 2008»
13 years 9 months ago
Maximal Quasi-Bicliques with Balanced Noise Tolerance: Concepts and Co-clustering Applications
The rigid all-versus-all adjacency required by a maximal biclique for its two vertex sets is extremely vulnerable to missing data. In the past, several types of quasi-bicliques ha...
Jinyan Li, Kelvin Sim, Guimei Liu, Limsoon Wong