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» Smoothing Gene Expression Using Biological Networks
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BMCBI
2004
205views more  BMCBI 2004»
13 years 7 months ago
A combinational feature selection and ensemble neural network method for classification of gene expression data
Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
Bing Liu, Qinghua Cui, Tianzi Jiang, Songde Ma
BIOSYSTEMS
2008
75views more  BIOSYSTEMS 2008»
13 years 7 months ago
Using matrix of thresholding partial correlation coefficients to infer regulatory network
DNA arrays measure the expression levels for thousands of genes simultaneously under different conditions. These measurements reflect many aspects of the underlying biological pro...
Lide Han, Jun Zhu
WILF
2005
Springer
194views Fuzzy Logic» more  WILF 2005»
14 years 29 days ago
Learning Bayesian Classifiers from Gene-Expression MicroArray Data
Computing methods that allow the efficient and accurate processing of experimentally gathered data play a crucial role in biological research. The aim of this paper is to present a...
Andrea Bosin, Nicoletta Dessì, Diego Libera...
ISBRA
2009
Springer
14 years 2 months ago
Integrating Multiple-Platform Expression Data through Gene Set Features
Abstract. We demonstrate a set-level approach to the integration of multiple platform gene expression data for predictive classification and show its utility for boosting classi...
Matej Holec, Filip Zelezný, Jirí Kl&...
IJSI
2008
122views more  IJSI 2008»
13 years 7 months ago
Mining Gene Expression Data using Domain Knowledge
Biology is now an information-intensive science and various research areas, like molecular biology, evolutionary biology or environmental biology, heavily depend on the availabilit...
Nicolas Pasquier, Claude Pasquier, Laurent Brisson...