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» Using a logical model to predict the growth of yeast
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BMCBI
2008
83views more  BMCBI 2008»
13 years 5 months ago
Prioritization of gene regulatory interactions from large-scale modules in yeast
Background: The identification of groups of co-regulated genes and their transcription factors, called transcriptional modules, has been a focus of many studies about biological s...
Ho-Joon Lee, Thomas Manke, Ricardo Bringas, Martin...
CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
13 years 11 months ago
Learning Yeast Gene Functions from Heterogeneous Sources of Data Using Hybrid Weighted Bayesian Networks
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Xutao Deng, Huimin Geng, Hesham H. Ali
BMCBI
2008
118views more  BMCBI 2008»
13 years 5 months ago
Inferring transcriptional compensation interactions in yeast via stepwise structure equation modeling
Background: With the abundant information produced by microarray technology, various approaches have been proposed to infer transcriptional regulatory networks. However, few appro...
Grace S. Shieh, Chung-Ming Chen, Ching-Yun Yu, Jui...
JCB
2008
90views more  JCB 2008»
13 years 5 months ago
A Simple Model of the Modular Structure of Transcriptional Regulation in Yeast
Resolving the general organizational principles that govern the interactions during transcriptional gene regulation has great relevance for understanding disease progression, biof...
Vladimir Filkov, Nameeta Shah
BMCBI
2006
110views more  BMCBI 2006»
13 years 5 months ago
Modelling the network of cell cycle transcription factors in the yeast Saccharomyces cerevisiae
Background: Reverse-engineering regulatory networks is one of the central challenges for computational biology. Many techniques have been developed to accomplish this by utilizing...
Shawn Cokus, Sherri Rose, David Haynor, Niels Gr&o...