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» Inferring gene regression networks with model trees
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BMCBI
2006
216views more  BMCBI 2006»
15 years 6 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
15 years 11 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»
16 years 20 days 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»
15 years 11 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»
15 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