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BMCBI
2006
120views more  BMCBI 2006»
13 years 7 months ago
An improved distance measure between the expression profiles linking co-expression and co-regulation in mouse
Background: Many statistical algorithms combine microarray expression data and genome sequence data to identify transcription factor binding motifs in the low eukaryotic genomes. ...
Ryung S. Kim, Hongkai Ji, Wing Hung Wong
EMO
2005
Springer
108views Optimization» more  EMO 2005»
14 years 1 months ago
Multi-objective Model Optimization for Inferring Gene Regulatory Networks
With the invention of microarray technology, researchers are able to measure the expression levels of ten thousands of genes in parallel at various time points of a biological proc...
Christian Spieth, Felix Streichert, Nora Speer, An...
BMCBI
2011
13 years 2 months ago
Using Stochastic Causal Trees to Augment Bayesian Networks for Modeling eQTL Datasets
Background: The combination of genotypic and genome-wide expression data arising from segregating populations offers an unprecedented opportunity to model and dissect complex phen...
Kyle C. Chipman, Ambuj K. Singh
JMLR
2006
103views more  JMLR 2006»
13 years 7 months ago
MinReg: A Scalable Algorithm for Learning Parsimonious Regulatory Networks in Yeast and Mammals
In recent years, there has been a growing interest in applying Bayesian networks and their extensions to reconstruct regulatory networks from gene expression data. Since the gene ...
Dana Pe'er, Amos Tanay, Aviv Regev
KDD
2009
ACM
230views Data Mining» more  KDD 2009»
14 years 2 days ago
Grouped graphical Granger modeling methods for temporal causal modeling
We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Ros...