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» Data Mining for Genetics: A Genetic Algorithm Approach
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154
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BMCBI
2011
14 years 10 months ago
Learning genetic epistasis using Bayesian network scoring criteria
Background: Gene-gene epistatic interactions likely play an important role in the genetic basis of many common diseases. Recently, machine-learning and data mining methods have be...
Xia Jiang, Richard E. Neapolitan, M. Michael Barma...
129
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BMCBI
2010
208views more  BMCBI 2010»
15 years 3 months ago
A multi-filter enhanced genetic ensemble system for gene selection and sample classification of microarray data
Background: Feature selection techniques are critical to the analysis of high dimensional datasets. This is especially true in gene selection from microarray data which are common...
Pengyi Yang, Bing Bing Zhou, Zili Zhang, Albert Y....
BMCBI
2005
98views more  BMCBI 2005»
15 years 3 months ago
InterferenceAnalyzer: Tools for the analysis and simulation of multi-locus genetic data
Background: Good statistical models for analyzing and simulating multilocus recombination data exist but are not accessible to many biologists because their use requires reasonabl...
Lalitha Viswanath, Elizabeth A. Housworth
152
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BIODATAMINING
2008
120views more  BIODATAMINING 2008»
15 years 3 months ago
Filling the gap between biology and computer science
This editorial introduces BioData Mining, a new journal which publishes research articles related to advances in computational methods and techniques for the extraction of useful ...
Jesús S. Aguilar-Ruiz, Jason H. Moore, Mary...
GECCO
2004
Springer
166views Optimization» more  GECCO 2004»
15 years 9 months ago
Evolutionary Ensemble for Stock Prediction
We propose a genetic ensemble of recurrent neural networks for stock prediction model. The genetic algorithm tunes neural networks in a two-dimensional and parallel framework. The ...
Yung-Keun Kwon, Byung Ro Moon