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» Bayesian Networks Learning for Gene Expression Datasets
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KDD
1994
ACM
123views Data Mining» more  KDD 1994»
15 years 3 months ago
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data
We describe scoring metrics for learning Bayesian networks from a combination of user knowledge and statistical data. We identify two important properties of metrics, which we cal...
David Heckerman, Dan Geiger, David Maxwell Chicker...
TCBB
2010
176views more  TCBB 2010»
14 years 10 months ago
Feature Selection for Gene Expression Using Model-Based Entropy
—Gene expression data usually contain a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes that best...
Shenghuo Zhu, Dingding Wang, Kai Yu, Tao Li, Yihon...
ECAI
2004
Springer
15 years 5 months ago
Exploiting Association and Correlation Rules - Parameters for Improving the K2 Algorithm
A Bayesian network is an appropriate tool to deal with the uncertainty that is typical of real-life applications. Bayesian network arcs represent statistical dependence between dif...
Evelina Lamma, Fabrizio Riguzzi, Sergio Storari
BMCBI
2006
128views more  BMCBI 2006»
14 years 11 months ago
An interactive tool for visualization of relationships between gene expression profiles
Background: Application of phenetic methods to gene expression analysis proved to be a successful approach. Visualizing the results in a 3-dimentional space may further enhance th...
Peter Ruzanov, Steven J. M. Jones
BMCBI
2008
202views more  BMCBI 2008»
14 years 12 months ago
Network motif-based identification of transcription factor-target gene relationships by integrating multi-source biological data
Background: Integrating data from multiple global assays and curated databases is essential to understand the spatiotemporal interactions within cells. Different experiments measu...
Yuji Zhang, Jianhua Xuan, Benildo de los Reyes, Ro...