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» Genetic Algorithms for Component Analysis
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136
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BMCBI
2004
208views more  BMCBI 2004»
15 years 3 months ago
Hybrid clustering for microarray image analysis combining intensity and shape features
Background: Image analysis is the first crucial step to obtain reliable results from microarray experiments. First, areas in the image belonging to single spots have to be identif...
Jörg Rahnenführer, Daniel Bozinov
JMLR
2012
13 years 6 months ago
Structured Sparse Canonical Correlation Analysis
In this paper, we propose to apply sparse canonical correlation analysis (sparse CCA) to an important genome-wide association study problem, eQTL mapping. Existing sparse CCA mode...
Xi Chen, Han Liu, Jaime G. Carbonell
111
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GECCO
2010
Springer
141views Optimization» more  GECCO 2010»
15 years 6 months ago
Today/future importance analysis
SBSE techniques have been widely applied to requirements selection and prioritization problems in order to ascertain a suitable set of requirements for the next release of a syste...
Yuanyuan Zhang, Enrique Alba, Juan J. Durillo, Sig...
AEI
2005
99views more  AEI 2005»
15 years 3 months ago
Comparison among five evolutionary-based optimization algorithms
Evolutionary algorithms (EAs) are stochastic search methods that mimic the natural biological evolution and/or the social behavior of species. Such algorithms have been developed ...
Emad Elbeltagi, Tarek Hegazy, Donald E. Grierson
143
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GECCO
2006
Springer
220views Optimization» more  GECCO 2006»
15 years 7 months ago
Comparing evolutionary algorithms on the problem of network inference
In this paper, we address the problem of finding gene regulatory networks from experimental DNA microarray data. We focus on the evaluation of the performance of different evoluti...
Christian Spieth, Rene Worzischek, Felix Streicher...