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- Universidade do Estado do Rio de JaneiroBR10 papers
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4 papers · 1 filter
Comparative analysis of module-based versus direct methods for reverse-engineering transcriptional regulatory networks
Tom Michoel, Riet De Smet, Anagha Joshi +2
We have compared a recently developed module-based algorithm LeMoNe for reverse-engineering transcriptional regulatory networks to a mutual information based direct algorithm CLR,…
Reverse-engineering transcriptional modules from gene expression data
Tom Michoel, Riet De Smet, Anagha Joshi +2
"Module networks" are a framework to learn gene regulatory networks from expression data using a probabilistic model in which coregulated genes share the same parameters and condit…
Module networks revisited: computational assessment and prioritization of model predictions
Anagha Joshi, Riet De Smet, Kathleen Marchal +2
The solution of high-dimensional inference and prediction problems in computational biology is almost always a compromise between mathematical theory and practical constraints such…
Validating module network learning algorithms using simulated data
Tom Michoel, Steven Maere, Eric Bonnet +8
In recent years, several authors have used probabilistic graphical models to learn expression modules and their regulatory programs from gene expression data. Here, we demonstrate…