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» Inferring gene regression networks with model trees
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BMCBI
2006
216views more  BMCBI 2006»
13 years 8 months ago
Machine learning approaches to supporting the identification of photoreceptor-enriched genes based on expression data
Background: Retinal photoreceptors are highly specialised cells, which detect light and are central to mammalian vision. Many retinal diseases occur as a result of inherited dysfu...
Haiying Wang, Huiru Zheng, David Simpson, Francisc...
IEAAIE
2004
Springer
14 years 2 months ago
Data Mining Approach for Analyzing Call Center Performance
Abstract. The aim of our research was to apply well-known data mining techniques (such as linear neural networks, multi-layered perceptrons, probabilistic neural networks, classifi...
Marcin Paprzycki, Ajith Abraham, Ruiyuan Guo, Srin...
WABI
2009
Springer
124views Bioinformatics» more  WABI 2009»
14 years 3 months ago
Mimosa: Mixture Model of Co-expression to Detect Modulators of Regulatory Interaction
Background: Functionally related genes tend to be correlated in their expression patterns across multiple conditions and/or tissue-types. Thus co-expression networks are often use...
Matthew Hansen, Logan Everett, Larry Singh, Sridha...
ICT
2004
Springer
120views Communications» more  ICT 2004»
14 years 2 months ago
Scalable End-to-End Multicast Tree Fault Isolation
We present a novel protocol, M3L, for multicast tree fault isolation based purely upon end-to-end information. Here, a fault is a link with a loss rate exceeding a specified thres...
Timur Friedman, Donald F. Towsley, James F. Kurose
CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
14 years 2 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