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» Linear Modeling of Genetic Networks from Experimental Data
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GECCO
2005
Springer
101views Optimization» more  GECCO 2005»
15 years 3 months ago
A scalable parallel genetic algorithm for x-ray spectroscopic analysis
We use a parallel multi-objective genetic algorithm to drive a search and reconstruction spectroscopic analysis of plasma gradients in inertial confinement fusion (ICF) implosion...
Kai Xu, Sushil J. Louis, Roberto C. Mancini
WOB
2004
14 years 11 months ago
An Integrated Model for Cellular Analysis
ABSTRACT. We present the MOlecular NETwork (MONET) ontology as a model to integrate data from different networks that govern cell function. To achieve this, different existing onto...
Eduardo Battistella, José Souza, Clá...
BMCBI
2007
171views more  BMCBI 2007»
14 years 9 months ago
Classification of microarray data using gene networks
Background: Microarrays have become extremely useful for analysing genetic phenomena, but establishing a relation between microarray analysis results (typically a list of genes) a...
Franck Rapaport, Andrei Zinovyev, Marie Dutreix, E...
NIPS
2000
14 years 11 months ago
Learning Switching Linear Models of Human Motion
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. Effective models of human dynamics can be learned from motion capture data usi...
Vladimir Pavlovic, James M. Rehg, John MacCormick
ESANN
1998
14 years 11 months ago
Recurrent SOM with local linear models in time series prediction
Recurrent Self-Organizing Map (RSOM) is studied in three di erent time series prediction cases. RSOM is used to cluster the series into local data sets, for which corresponding lo...
Timo Koskela, Markus Varsta, Jukka Heikkonen, Kimm...